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NCJ

Number:

178919 

Title: Mapping Crime: Principle and Practice

Author(s): Keith Harries Ph.D.

Date

Published:

1999

Page Count: 204

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Agency:

National Institute of Justice (NIJ)

Washington, DC 20531

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Type: Policy/Procedure Handbook/Manual

Format: Document

Language: English

Country: United States of America

Annotation: This is an introduction to the science of crime mapping, visualizing crime data through the medium of

maps.

Abstract: The volume is divided into six chapters, each with a summary section. The chapters, with selected

sub-categories, are: (1) Context and Concepts (mapping as art, science and abstraction of reality,

map elements, other theoretical perspectives, cartograms); (2) What Crime Maps Do and How They

Do It (examples of thematic maps, exploratory spatial data analysis, map design); (3) Maps That

Speak to the Issues (maps in support of community oriented policing and problem oriented policing,

courts and corrections, community organizations); (4) Mapping Crime and Geographic Information

Systems (the GIS revolution and GIS perspective, geocoding, how to create new indicators); (5)

Synthesis and Applications (Synthesis 2000, mapping applications for the millennium, crime analysis

and the census); and (6) Crime Mapping Futures (geographic profiling, digital aerial photography in

policing, the integration of GIS and GPS). Figures, notes, tables, references, appendix, index

Main

Term(s):

Criminology

Index

Term(s):

Community policing; Crime patterns; Crime Statistics; Crime surveys; Geographic distribution of

crime; Geographic information systems (GIS); NIJ final report; Photography techniques; ProblemOriented Policing; Statistical analysis

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DEPARTMENT OF JUSTICE

OFF ICE OF JUSTICE PROGRAMS

BJA NI J OJJDP BJS OVC

U.S. Department of Justice

Office of Justice Programs

National Institute of Justice

MAPPING 

CRIME

MAPPING 

CRIME

PRINCIPLE AND 

PRACTICE
U.S. Department of Justice

Office of Justice Programs

810 Seventh Street N.W.

Washington, DC 20531

Janet Reno

Attorney General

Daniel Marcus

Acting Associate Attorney General

Laurie Robinson

Assistant Attorney General

Noël Brennan

Deputy Assistant Attorney General

Jeremy Travis

Director, National Institute of Justice

Office of Justice Programs National Institute of Justice

World Wide Web Site World Wide Web Site 

http://www.ojp.usdoj.gov http://www.ojp.usdoj.gov/nij
About the National Institute of Justice

The National Institute of Justice (NIJ), a component of the Office of Justice Programs, is the research agency of 

the U.S. Department of Justice. Created by the Omnibus Crime Control and Safe Streets Act of 1968, as amended,

NIJ is authorized to support research, evaluation, and demonstration programs, development of technology, and 

both national and international information dissemination. Specific mandates of the Act direct NIJ to:

● Sponsor special projects, and research and development programs, that will improve and strengthen the 

criminal justice system and reduce or prevent crime. 

● Conduct national demonstration projects that employ innovative or promising approaches for improving 

criminal justice. 

● Develop new technologies to fight crime and improve criminal justice. 

● Evaluate the effectiveness of criminal justice programs and identify programs that promise to be successful if 

continued or repeated. 

● Recommend actions that can be taken by Federal, State, and local governments as well as by private organizations

to improve criminal justice. 

● Carry out research on criminal behavior. 

● Develop new methods of crime prevention and reduction of crime and delinquency. 

In recent years, NIJ has greatly expanded its initiatives, the result of the Violent Crime Control and Law Enforcement

Act of 1994 (the Crime Act), partnerships with other Federal agencies and private foundations, advances in 

technology, and a new international focus. Some examples of these new initiatives:

● New research and evaluation are exploring key issues in community policing, violence against women, sentencing

reforms, and specialized courts such as drug courts. 

● Dual-use technologies are being developed to support national defense and local law enforcement needs. 

● The causes, treatment, and prevention of violence against women and violence within the family are being 

investigated in cooperation with several agencies of the U.S. Department of Health and Human Services. 

● NIJ’s links with the international community are being strengthened through membership in the United Nations 

network of criminological institutes; participation in developing the U.N. Criminal Justice Information Network;

initiation of UNOJUST (U.N. Online Justice Clearinghouse), which electronically links the institutes to the 

U.N. network; and establishment of an NIJ International Center. 

● The NIJ-administered criminal justice information clearinghouse, the world’s largest, has improved its 

online capability. 

● The Institute’s Drug Use Forecasting (DUF) program has been expanded and enhanced. Renamed ADAM 

(Arrestee Drug Abuse Monitoring), the program will increase the number of drug-testing sites, and its role 

as a “platform” for studying drug-related crime will grow. 

● NIJ’s new Crime Mapping Research Center will provide training in computer mapping technology, collect and

archive geocoded crime data, and develop analytic software. 

● The Institute’s program of intramural research has been expanded and enhanced. 

The Institute Director, who is appointed by the President and confirmed by the Senate, establishes the Institute’s 

objectives, guided by the priorities of the Office of Justice Programs, the Department of Justice, and the needs of 

the criminal justice field. The Institute actively solicits the views of criminal justice professionals and researchers 

in the continuing search for answers that inform public policymaking in crime and justice.
U.S. Department of Justice

Office of Justice Programs

National Institute of Justice

Washington, DC 20531

Official Business

Penalty for Private Use $300

SPECIAL STANDARD MAIL

POSTAGE & FEES PAID

DOJ/NIJ

PERMIT NO. G–91

Mapping Crime: Principle and Practice

Research Report
U.S. Department of Justice

Office of Justice Programs

810 Seventh Street N.W.

Washington, DC 20531

Janet Reno

Attorney General

Daniel Marcus

Acting Associate Attorney General

Laurie Robinson

Assistant Attorney General

Noël Brennan

Deputy Assistant Attorney General

Jeremy Travis

Director, National Institute of Justice

Office of Justice Programs National Institute of Justice

World Wide Web Site World Wide Web Site 

http://www.ojp.usdoj.gov http://www.ojp.usdoj.gov/nij
Mapping Crime: 

Principle and Practice

Keith Harries, Ph.D.

December 1999

NCJ 178919
Jeremy Travis

Director

Nancy La Vigne

Program Monitor

This project was supported by Grant No. 98–LB–VX–0009 awarded by the National Institute of

Justice, Office of Justice Programs, U.S. Department of Justice. Points of view in this document

are those of the author and do not necessarily represent the official position or policies of the U.S.

Department of Justice.

The National Institute of Justice is a component of the Office of Justice Programs, which also includes the

Bureau of Justice Assistance, the Bureau of Justice Statistics, the Office of Juvenile Justice and Delinquency

Prevention, and the Office for Victims of Crime.

Cover Credits

Clockwise, starting with upper left corner:

Map by Lodha and Verma, 1999

Map by Jeff Stith and the Wilson, North Carolina, Police Department

Map by Wilpen Gorr, Heinz School of Public Policy and

Management, Carnegie Mellon University, Pittsburgh, Pennsylvania

Map by Susan Wernicke, Overland Park, Kansas, Police Department

Map by ASDI Technologies, Colorado Springs, Colorado

Map by Jeff Stith and the Wilson, North Carolina, Police Department
iii

Mapping Crime: Principle and Practice

Acknowledgments

Without the generous cooperation of

many people in various settings, including

police departments and universities, the

variety of examples and particularly illustrations presented in this guide would not

have been possible. Some individuals who

should have been acknowledged below

may have been inadvertently omitted, and

I apologize if that is the case. Among

those who must be singled out for special

recognition are the following (in alphabetical order):

Al Ball, Office of Community Oriented

Policing Services (COPS) Regional

Institute, Cincinnati, Ohio; Rachel Boba,

Tempe Police Department, Tempe,

Arizona; Chris Bruce, Cambridge Police

Department, Cambridge, Massachusetts;

Jim Bueermann, Redlands Police

Department, Redlands, California; 

Philip Canter, Baltimore County Police

Department, Towson, Maryland; Peter

Dana, University of Texas, Austin, Texas;

Wilpen Gorr, Heinz School, Carnegie

Mellon University, Pittsburgh,

Pennsylvania; Elizabeth Groff, Crime

Mapping Research Center, National

Institute of Justice, Washington, D.C.; Hal

Holtzman, U.S. Department of Housing

and Urban Development, Washington,

D.C.; James LeBeau, Southern Illinois

University, Carbondale, Illinois; Suresh K.

Lodha, University of California, Santa

Cruz, California; Mark Mattson, Temple

University, Philadelphia, Pennsylvania;

Tom McEwen, Institute for Law and

Justice, Alexandria, Virginia; Phillip G.

McGuire, New York City Police

Department, New York, New York; Sara

McLafferty, Hunter College, New York,

New York; Robert Moland, St. Petersburg

Police Department, St. Petersburg, Florida;

Tracy Molfino, Salinas Police Department,

Salinas, California; Lew Nelson,

Environmental Systems Research

Institute, Inc., Redlands, California; Mike

Neumann, Cincinnati Police Department,

Cincinnati, Ohio; Andreas Olligschlaeger,

Carnegie Mellon University, Pittsburgh,

Pennsylvania; George Rengert, Temple

University, Philadelphia, Pennsylvania; 

D. Kim Rossmo, Vancouver Police

Department, Vancouver, British Columbia,

Canada; Mark Stallo, Dallas Police

Department, Dallas, Texas; Gerry Tallman,

Overland Park Police Department,

Overland Park, Kansas; Deb Thomas,

University of South Carolina, Columbia,

South Carolina; Arvind Verma, Indiana

University, Bloomington, Indiana; Julie

Wartell, Institute for Law and Justice,

Alexandria, Virginia; John Werner, Mesa

Police Department, Mesa, Arizona; 

Susan Wernicke, Overland Park Police

Department, Overland Park, Kansas; Doug

Williamson, Center for Applied Studies of

the Environment (CAPSE), City University

of New York, New York, New York. 
Acknowledgments

I am particularly grateful to Nancy 

La Vigne, director of the National Institute

of Justice (NIJ) Crime Mapping Research

Center, who facilitated this project. Several

reviewers, anonymous and otherwise,

provided invaluable insight that has been

incorporated. I am also grateful to my colleague Tom Rabenhorst, former cartographic

editor of Annals of the Association of

American Geographers, who edited the

maps. 

Ultimately, all these efforts to spread the

blame are in vain, and the author accepts

full responsibility for errors, omissions,

and misinterpretations.

iv
v

Mapping Crime: Principle and Practice

Foreword

In 1997, when the National Institute of

Justice (NIJ) was planning to create its

Crime Mapping Research Center (CMRC),

we convened a 2-day strategic planning

meeting to seek advice on the Center’s

goals, direction, and mission. Before the

meeting, we had assumed that many

agencies were already using mapping and

that NIJ’s goal would be to encourage the

field to move beyond descriptive mapping

(e.g., pin maps) toward analytic mapping.

The meeting helped us recognize that

another goal must be to assist the large

number of agencies that are not using

mapping. 

Keith Harries, who received one of the

first grants from CMRC, has prepared this

comprehensive guide for agencies that are

in the early stages of using geographic

information systems (GIS). His words are

directed to law enforcement professionals

who have a little knowledge about GIS

and want to learn more about its benefits

and limitations. 

He has collected more than 110 maps to

illustrate how GIS is used. These pictures

express the truth of the phrase “one picture is worth a thousand words.” 

Dr. Harries’ guide is not designed to stand

alone. Law enforcement agencies will

need other curriculum materials as well—

especially software manuals—but it will

be a starting place. Additional materials

and links to other sources of information

can be found at CMRC’s World Wide Web

site (http://www.ojp.usdoj.gov/cmrc). 

As a clearinghouse of information about

crime mapping, CMRC also sponsors a listserv (listproc@aspensys.com), which has

more than 640 subscribers, and an annual

conference, which draws more than 700

attendees. 

Today about 13 percent of law enforcement agencies are using GIS regularly to

analyze their crime problems, and we are

certain to see this number increase significantly as more and more agencies begin

using computerized crime mapping to

identify and solve their crime problems.

We hope this guide will help them get

started. For agencies that are already

using crime mapping technology, we 

hope this guide will spark ideas about

new ways to use it. 

Jeremy Travis

Director

National Institute of Justice
vii

Mapping Crime: Principle and Practice

Preface

This guide introduces the science of crime

mapping to police officers, crime analysts,

and other people interested in visualizing

crime data through the medium of maps.

Presumably most readers will be working

in law enforcement agencies, broadly

interpreted to include courts, corrections,

the military police, and Federal agencies

such as the FBI, U.S. Bureau of Alcohol,

Tobacco and Firearms, National Park

Service, U.S. Customs Service, and U.S.

Secret Service, as well as police departments. The material is designed primarily

for those who know little or nothing about

mapping crime and who are motivated to

learn more.

This is not a guide to software. Nowhere

is there more than a word or two on how

to do anything technical involving a computer. A purely technical guide would

quickly be out of date, and a guide that

served one set of software devotees would

not serve others. Technical guidance is

best sought from the manuals and interest

groups specific to each software package.

What will be found here is a broad

approach addressing the kinds of questions crime mapping can answer and how,

in general terms, it can answer them.

Caveats are given from time to time,

notably the caution against uncritically

accepting all the default settings that

crime mapping software so conveniently

provides.

Most readers will not read this guide from

cover to cover. Some will concentrate on

application-oriented material. Others will

have an interest in the history of crime

mapping, realizing that where we have

been can help us figure out where we 

are going.

The presentation employed in this guide

leans heavily on examples. Indeed, the

guide is made up of examples with the

words draped around them. Crime analysts

and researchers from across the United

States and from Canada and the United

Kingdom have contributed. Without their

help, this guide would be an empty shell.

I am extremely grateful to all who donated

their work so graciously, and a partial listing of these kind souls is found in the

acknowledgments.

Keith Harries
ix

Mapping Crime: Principle and Practice

Contents

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Chapter 1: Context and Concepts . . . . . . . . . . . . . . . . . . . . . . . . 1

From pins to computers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Ancient history: Cartography and crime mapping . . . . . . . . . . . . . . . . . . . . . . . . 3

Mapping as a special case of data visualization. . . . . . . . . . . . . . . . . . . . . . . . . . 6

Mapping as art and science. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Maps as abstractions of reality: Benefits and costs . . . . . . . . . . . . . . . . . . . . . . 10

Crime incidents: Measuring time and space. . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Map projection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Coordinate systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Map elements: The usual bits and pieces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Types of map information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Maps of crime: Thematic maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Data, maps, and patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Other theoretical perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

A note on cartograms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Reminder: Information is inevitably lost in the process of abstraction . . . . . . . . . 30

A note on the maps in this guide. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Chapter 2: What Crime Maps Do and How They Do It . . . . . . . . . 35

What crime maps do . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

How crime maps do what they do . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Choosing a crime map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
Contents

Examples of thematic maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Classifying map information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Maps and statistics: Exploratory spatial data analysis . . . . . . . . . . . . . . . . . . . . 53

Map design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Design, abstraction, and legibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Chapter 3: Maps That Speak to the Issues . . . . . . . . . . . . . . . . . 67

Patrol officers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Investigators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Police managers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

Maps in support of community oriented policing and problem oriented policing . . 80

Maps and community policing: The city of Redlands, California, approach. . . . . . 82

Courts and corrections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

Policymakers: The medium and the message . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Community organizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

Chapter 4: Mapping Crime and Geographic Information Systems . 91

The GIS revolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

The GIS perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

Spatially enabling the data: What is geocoding? . . . . . . . . . . . . . . . . . . . . . . . . 97

Data selecting, filtering, and mapping according to useful criteria . . . . . . . . . . . 100

Selecting and displaying specific information . . . . . . . . . . . . . . . . . . . . . . . . . 100

Using GIS to measure from maps: Aggregating data . . . . . . . . . . . . . . . . . . . . 105

Derivative measures: How to create new indicators . . . . . . . . . . . . . . . . . . . . . 109

GIS as a tool for data integration and exploration . . . . . . . . . . . . . . . . . . . . . . 110

Hot spots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

Buffering: Meaning and applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118

Data, data, everywhere: What’s an analyst to do?. . . . . . . . . . . . . . . . . . . . . . 121

Cautions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

x
xi

Mapping Crime: Principle and Practice

Chapter 5: Synthesis and Applications . . . . . . . . . . . . . . . . . . . 127

Synthesis 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127

Mapping applications for the millennium . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136

Crime analysis and the census. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148

Chapter 6: Crime Mapping Futures . . . . . . . . . . . . . . . . . . . . . . 151

Geographic profiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152

High-resolution GIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155

Forecasting: Complex statistical methods and crime mapping . . . . . . . . . . . . . . 155

Digital aerial photography in policing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

The Integration of GIS and GPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169

Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
1

Mapping Crime: Principle and Practice

Chapter 1

Chapter 1:

Context and

Concepts

From pins to computers

Crime mapping has long been an integral part of the

process known today as crime analysis. The New

York City Police Department, for example, has traced

the use of maps back to at least 1900. The traditional

crime map was a jumbo representation of a jurisdiction

with pins stuck in it (figure 1.1). The old pin maps

were useful for showing where crimes occurred, but

they had serious limitations. As they were updated,

the prior crime patterns were lost. While raw data

could be archived, maps could not, except perhaps 

by photographing them.1 The maps were static; they

could not be manipulated or queried. For example, it

would have been difficult to track a series of robberies

that might overlap the duration (a week or month) of

a pin map. Also, pin maps could be quite difficult to

read when several types of crime, usually represented

by pins of different colors, were mixed together. Pin

maps occupied considerable wall space; Canter (1997)

noted that to make a single wall map of the 610

square miles of Baltimore County, 12 maps had to be

joined, covering 70 square feet. Thus pin maps had

limited value—they could be used effectively but only

for a short time. However, pin maps are sometimes

still used today because their large scales allow

patterns to be seen over an entire jurisdiction in detail.

Today, “virtual” pin maps can be made on the 
Context and Concepts

computer, using pins or other icons as

symbols (figure 1.2). 

The manual approach of pin mapping

gave way during the past decade or so to

computer mapping—specifically, desktop

computer mapping. For decades before

desktop computer mapping, the process

was carried out on gigantic mainframe

computers using an extremely laborintensive process. First, much labor was

involved in describing the boundaries of

the map with numbered coordinates on

punched cards. Then came the labor of

keypunching the cards, followed by a 

similar process of coding and keypunching

to put the data on the map. 

Recognizing all the work needed to 

produce a map on the computer, many

potential cartographers2 (mapmakers)

concluded that computer mapping was too

labor intensive. They were right—it was 

a “royal pain.” It was productive only 

if many maps were needed (making it

worthwhile to prepare the base map, or

boundary map, of the jurisdiction), and 

if the personnel necessary to do the data

coding and keypunching were available.

Few organizations could afford the luxury.

Since the mid-1980s, and particularly

since the early 1990s, when computer

processing speed increased dramatically,

desktop mapping became commonplace

2 Chapter 1

Figure 1.1

Pin maps.

Source: Keith Harries.

University of Maryland,

Baltimore County,

Baltimore, Maryland.

Figure 1.2

A “virtual” pin map.

Source: SanGIS and

the San Diego Police

Department Crime

Analysis Unit.
and fast, aided and abetted by the concurrent availability of cheap color printers.

What a partnership! Only a generation

earlier, maps on paper (as compared with

the pin maps on walls in police departments) had been drawn by hand using

india ink3 and special pens, with templates

for lettering. If a mistake was made, the

lettering had to be scraped off the paper

with a razor blade. If shading was needed,

Zipatone® patterns were cut to fit the area

and burnished to stick. Those were the

days? For character building, perhaps!

What does all this have to do with mapping crime today? A newfound access to

desktop mapping means that more individuals than ever before have the task—

or opportunity—to produce computer

maps. Also the huge demand for maps

means that most crime analysts, police

officers, and others involved in mapping

crime have received no formal training in

mapmaking—the science called cartography. A body of accepted and useful principles and practices has evolved over the

long history of mapmaking. Most cartography texts contain those principles but

have no regard for the special needs of

the crime analyst, police officer, manager,

or community user of crime maps. The

goal of this guide, therefore, is to provide 

a guide to cartography that is adapted to

specialized needs and speaks the cartographer’s language.

This guide is not intended to stand alone,

isolated from evolving developments in

crime mapping. Ideally, it should be used

in conjunction with other materials and

approaches. In 1998, for example, a

group working with the support of the

Crime Mapping Research Center (CMRC)

at the National Institute of Justice developed a national curriculum for crime mapping. Much information contained in this

guide can be found fleshed out in the curriculum and other materials disseminated

by CMRC. Readers are strongly encouraged to visit the CMRC Web site at

http://www.ojp.usdoj.gov/cmrc. 

Ancient history:

Cartography and 

crime mapping 

Conclusive evidence from clay tablets

found in Iraq proves that maps have 

been around for several thousand years—

perhaps tens of millennia (Campbell,

1993). Evidently, the need to display 

geographic data is basic and enduring.

Nowhere is the need for maps more compelling than in the field of navigation,

whether for an epic around-the-world

voyage or for a rookie cop’s struggle to

find an address in a city map book. Maps

for navigation can be matters of life and

death, and the inability of early navigators to locate themselves accurately on the

3

Mapping Crime: Principle and Practice

Chapter 1

Maps

■ Are pictures of information about areas and places. 

■ Help us visualize data. 

■ Are like the proverbial pictures worth a thousand words. 

■ Enable information to be seen at a glance.
Context and Concepts

surface of the Earth have often spelled

disaster, as described vividly in Dava

Sobel’s book Longitude (1995).

Fortunately, crime mappers do not have 

to be concerned about such epic matters.

However, mapping crime is a scientific

activity—an application of the broader 

scientific field of cartography, which has

undergone a transformation with the

advent of geographic information systems

(GIS). Many mapmakers now see cartography as a branch of information technology. A decade or so ago, cartography was

much broader in scope than GIS with

applications in fields as diverse as surveying, navigation of all kinds (including 

orienteering and highway mapping), 

geology, space exploration, environmental

management, tourism, and urban planning. Today, however, the convergence 

of cartography and GIS is nearly complete.

Both are tools in a broad range of applications, reflecting the most important use of

maps—to communicate information. 

Crime mapping, as noted at the beginning

of this chapter, has quite a long history.

Phillips (1972) pointed out that “hundreds of spatially oriented studies of crime

and delinquency have been written by

sociologists and criminologists since about

1830. . .” and recognized three major

schools:

■ The cartographic or geographic

school dominated between 1830 and

1880, starting in France and spreading

to England. This work was based on

social data, which governments were

beginning to gather. Findings tended 

to center on the influence of variables

such as wealth and population density

on levels of crime. 

■ The typological school dominated

between the cartographic period and

the ecological period that would follow

in the 20th century. The typologists

focused on the relationship between

the mental and physical characteristics

of people and crime.

■ The social ecology school concentrated on geographic variations in social

conditions under the assumption that

they were related to patterns of crime. 

The social ecologists recognized and classified areas in cities with similar social

characteristics. Shaw and McKay (1942)

produced a classic analysis on juvenile

delinquency in Chicago. This work is generally recognized as the landmark piece of

research involving crime mapping in the

first half of the 20th century. Shaw and

McKay mapped thousands of incidents 

of juvenile delinquency and analyzed 

relationships between delinquency and

various social conditions. Work by the

“Chicago school” of researchers also delineated an urban model based on concentric

zones, the first attempt to develop a theory to explain the layout of cities (Burgess,

1925). Other significant contributors to

the ecological school included Lander

(1954), Lottier (1938), and Boggs (1966).

Most likely, the first use of computerized

crime mapping in applied crime analysis

occurred in the mid-1960s in St. Louis

(McEwen and Research Management

Associates, Inc., 1966; Pauly, McEwen,

and Finch, 1967; Carnaghi and McEwen,

1970; for more discussion, see chapter 4).

Ironically, professional geographers were

late getting into the act. Early contributions came from Lloyd Haring (who

organized a seminar on the geography 

4 Chapter 1
of crime at Arizona State University

around 1970), David Herbert in the

United Kingdom, Harries (1971, 1973,

1974), Phillips (1972), Pyle et al. (1974),

Lee and Egan (1972), Rengert (1975),

Capone and Nichols (1976), and others.

Among the most remarkable (and little

known) pieces of research emphasizing

crime mapping were Schmid and Schmid’s

Crime in the State of Washington (1972)

and Frisbie et al.’s Crime in Minneapolis:

Proposals for Prevention (1997)(figures

1.3 and 1.4). The latter, in particular, was

notable for bridging the gap between academic crime mapping and analysis/applications specifically aimed at crime prevention. Early computer mapping efforts used

line printers as their display devices, so

their resolution was limited to the physical

size of the print characters. This precluded

the use of computer maps for the representation of point data, at least until plotters that were able to draw finer lines and

point symbols came into more general

use. (For an excellent review of early map

applications in crime prevention, see

Weisburd and McEwen, 1997, pp. 1–26.)

5

Mapping Crime: Principle and Practice

Chapter 1

Figure 1.3 

A map showing home

addresses of male arrestees

charged with driving under the

influence, Seattle, Washington.

1968–70. 

Source: Schmid and Schmid,

1972, figure 7.14, p. 311.

Figure 1.4

A map showing the rate of commercial robbery by census tract,

Minneapolis, Minnesota. Line

printer technology.

Source: Frisbie et al., 1977, 

figure 7.2, p. 122.
Context and Concepts

Even as late as 1980, the breakthrough

into widespread GIS-style crime mapping

was about a decade away. It was necessary to wait for improvements in desktop

computer capacity, printer enhancements,

and price reductions before desktop mapping could become an everyday, broadly

accepted phenomenon. 

To illustrate how matters have improved,

a snippet of personal history is offered. 

In April 1984, the author bought his first

personal computer, a Kaypro 10 manufactured by Digital Research, Inc. This 

wonder ran at 4 megahertz and had 

64 kilobytes of random access memory

(RAM) and a 10-megabyte hard drive.

(“How could you ever use all that storage?” friends asked.) It also had a tiny

monochrome display and ran on the 

CP/M operating system, the precursor of

Microsoft DOS. And all this for the rockbottom price of $2,795 in 1984 dollars.

The Silver Reed daisy wheel printer purchased to complement the computer was

$895 (extra daisy wheels were $22.50

each, tractor feed for paper was $160),

and the 300k-baud rate modem was

$535. After adding a few other knickknacks, getting started in personal computing cost almost $5,000 (again, in

1984 dollars).

By comparison, the typical RAM in 

1999 is perhaps 1,000 times larger (64

megabytes), the processor speed is 100

times faster (at least 400 megahertz), and

hard drives routinely are 100 times bigger

(10 gigabytes), all at a lower price. It was

this type of computing environment that

would facilitate the entry of GIS into law

enforcement (and elsewhere) and permit

cartographic principles and practices to be

used on a day-to-day basis. Mapping

crime has come into its own primarily

because of advances in computing that, 

in turn, have facilitated GIS applications.

Apart from all the obvious advantages, a

major benefit is that computer mapping

allows free rein to experiment, a luxury

denied in the old days of manual mapping. Are you wondering what a certain

map design would look like? Try it out.

You don’t like it? Start over and have a

new map in minutes. 

Mapping as a 

special case of 

data visualization

Desktop computing has put graphic tools

within the reach of virtually everyone.

Preparing a publication-quality graphic,

statistical or otherwise, was an arduous

process a generation ago. Today it is much

easier, although the process still demands

considerable care and effort. This new

ease and flexibility have broadened our 

perspective on graphics as tools for the

visualization of information. This has happened because people no longer have to

devote themselves to one specialized,

time-consuming methodology, such as

cartography. Now, maps can be produced

more easily, and the computer has in

effect freed people to produce other kinds

of graphics as needed, such as bar charts,

scatter diagrams, and pie charts.

The downside to such ease of production

is that it is just as easy to produce trash

as it is to create technical and artistic 

perfection. Famous graphics authority

Tufte (1983, chapter 5) referred to what

he called “non-data-ink,” “redundant6 Chapter 1
data-ink,” and “graphical paraphernalia”—all summed up by the term

“chartjunk,” a concept equally applicable

to maps and charts. An exemplary map,

according to Tufte, was prepared by

Joseph Minard in 1861 to depict the

decline of Napoleon’s army in Russia in

1812–13 (figure 1.5). Tufte noted that 

“it may well be the best statistical graphic

ever drawn” (Tufte, 1983, p. 40). What

makes it so good is that it shows six variables with extraordinary clarity and without the use of color variation. The width

of the bands is proportional to the number

of troops, starting with 424,000, which

was reduced to 100,000 by the time they

reached Moscow. The map shows attrition

on the return trip (with vertical rays

expressing temperatures on selected dates)

that left only 10,000 men still alive when

the army returned to the starting point. The

fact that the map illustrates the devastating loss of life further adds to its drama. 

Today’s simplified graphics-producing

environment helps put maps in perspective. Maps are but one way of representing information, and they are not always

the most appropriate mode. If information

about places is being represented, maps

may be the best format. However, if no

geographic (place-to-place) information is

present, such as when all the data for a

city are combined into one table, there is

nothing to map. The whole jurisdiction is

represented by one number (or several

numbers, each representing the city as a

whole), so the map, too, could portray

only one number. In this situation, a bar

chart simply showing the relative levels 

of each crime category would be the best

choice.

What does it mean to say that maps are a

form of visualization? Simply that a map

is data in a form that we can see all at

once. Books or tabulations of data are also

visualizations in the sense that we assimilate them visually, but they are laborintensive visualizations. Maps and other

graphics are essentially pictures of information, those proverbial pictures “worth a

thousand words.” If they are well done,

they convey their message more or less at

a glance.

Mapping as art 

and science

Like other forms of visualization, maps

are the outcome of scientific activity:

hypothesis formulation, data gathering,

7

Mapping Crime: Principle and Practice

Chapter 1

Figure 1.5

Minard’s 1861 

map of

Napoleon’s

advance to and

retreat from

Moscow.

Source: Tufte,

1983, p. 41.

Reproduced by

permission.
Context and Concepts

analysis, review of results, and evaluation

of whether the initial hypothesis should

be accepted or rejected in favor of a modified version. This cycle, known as the

hypothetic-deductive process, is used

throughout science as a fundamental tool.

It is a universal paradigm, or model, for

scientific investigation. 

Constructing a map involves taking a set

of data and making decisions consistent

with the hypothetic-deductive process.

Decisions need to be made about the kind

of map to be prepared, how symbols or

shading will look, how statistical information will be treated, and so forth. These

decisions must be based on the objective

to be achieved, including consideration of

the target audience. Certain scientific principles can be applied. For example, if we

are preparing a shaded map with a range

of statistical data to be divided equally,

then a simple formula can guide us:

Range in data values ÷ Number of classes.

Thus, if the range (difference between

maximum value and minimum value) of

data values is 50 and it has been determined that 4 classes, or “subranges,” of

data would be appropriate, each will span

12.5 units. This simple example demonstrates an elementary cartographic principle.

However, this science provides no help

with elements of map design, such as

choice of colors, symbols, or lettering, and

the arrangement of map elements on the

page or within a frame. These elements

are pieces of the art of cartography and

are just as important to the overall purpose

and effectiveness of the map as the scientific elements. A map that is scientifically

perfect may be ineffective if it is an artistic

disaster. 

Art and science may merge imperceptibly

and confound one another in unfortunate

ways. For example, oversized symbols or

lettering may draw attention to parts of

the map that should be understated or less

emphasized from a purely scientific perspective. A poor choice of colors or intervals for statistics can also make a big

difference. Thus the scientific mission of

the map can be subverted through inappropriate artistic choices, and poor choices

on the science side can similarly affect the

artistic elements. In cartography, as in

medicine, art and science are inseparable.

The perfect map blends art and science

into an effective tool of visual communication. Figure 1.6 shows elements of

weaker (middle figure) and stronger (bottom figure) map design. The chart (top

figure) known as a histogram accompanying the maps shows an approximately

normal (bell-shaped) distribution of scores

on an index representing the association

between violence and poverty in a neighborhood of Baltimore. The scores have a

mean, or average, of zero and a measure

of spread around the mean (standard

deviation) of 1.0. Technically, this means

that the census block groups in the range

–1.0 to +1.0 are not significantly different

from the average. Those with scores lower

than –1.0 or higher than +1.0 are considered relatively extreme. We may wish to

map the extremes because they could

convey information of value in community policing—areas with a strong link

between poverty and violence may warrant special allocations of crime prevention and social service resources.

8 Chapter 1
If the objective of the map is to represent

the high and low extremes, then the bottom figure does a much better job than

the middle one, both in terms of how the

data are divided and how they are symbolized with colors. The bottom figure

divides the data into standard deviation

units such that the blue and red values

are the focus of attention. In the middle

figure, the visual message is almost lost in

a combination of a poor choice of colors

and shading symbols and a confusing

division of the data into classes. The visual messages conveyed by the maps are

different, yet the underlying geographies

and statistics are identical. This example

emphasizes the importance of the map as

a medium for the interpretation of information. Subjective choices relating to both

the art and science content of the map are

critical.

Figure 1.6 also reminds us that it is just

as easy to lie with maps as it is to lie with

statistics. (Remember the three kinds of

lies: lies, damn lies, and statistics—and

maps, perhaps?) “Lying” may be a bit

strong. It is more likely that the compiler

of the map misleads readers by choosing

inappropriate designs rather than by

intentionally falsifying information. This

may happen on several levels, the most

basic being that the author of the map

created it to achieve an objective different

from that experienced by the readers.

Next are issues related to data manipulation and cartographic art. Ultimately, the

possibilities for misrepresentation and misinterpretation are virtually infinite. The

key question is whether these problems

are fatal flaws with respect to specific maps.

9

Mapping Crime: Principle and Practice

Chapter 1

Figure 1.6

Examples of maps with differing

impact depending on design.

Source: Keith Harries.
Context and Concepts

Maps as abstractions 

of reality: Benefits 

and costs

Maps try to display some aspect of reality.

But like books, movies, television, or

newspapers that try to do the same, they

fall short (figure 1.7). The only perfect

representation of reality is, after all, reality

itself. (“You had to be there.”) All else 

is, to a greater or lesser degree, an

abstraction. Abstractions present choices.

How much abstraction can we tolerate?

How much information can we afford to

lose? The fundamental tradeoff is:

■ More abstraction equals less information (farther from reality). 

■ Less abstraction equals more information (closer to reality). 

The tradeoff can also be viewed this way: 

■ More abstraction equals greater simplicity and legibility (more effective

visual communication).

■ Less abstraction equals greater complexity, less legibility (less effective

visual communication).

In our quest to represent reality as faithfully as possible, we may be tempted to

put too much “stuff” in our maps or other

graphics. This may give us maps that have

a lot of information but that may be illegible

junk heaps. Usually, the abstraction-reality

10 Chapter 1

Figure 1.7

Maps showing the contrast

between more abstraction

(“stick” streets—top) and less

abstraction (an aerial photograph

of the same area—bottom).

Source: Orthophotography:

Baltimore County, Maryland, GIS

Unit, March 19, 1995 (Phase II),

pixel size 1”, compilation scale

1” = 200’. Reproduced by 

permission.
tradeoff should tilt us in the direction of

simplicity. Better to have one or two

important points clearly understood than

to have utter confusion pushing readers

toward anger and frustration. Worse yet,

that confusion may cause readers to draw

incorrect conclusions. That outcome could

be worse than no map at all.

Consideration of this tradeoff should be

part of the map production process. With

practice, it will become “second nature”

and will not need much thought. But for

the novice, it is an important issue calling

for thought and perhaps discussion with

colleagues. Reading Tufte (1983, 1990)

will raise awareness.

Crime incidents:

Measuring time

and space

Crimes happen—everything happens—in

both time and space. Vasiliev (1996) has

suggested that time is a more difficult 

concept than space. Spaces and locations

can be seen and measured quite easily by

means of simple reference systems, such

as x-y coordinates. Time, however, is

harder to grasp, and maps have represented time in multiple ways (Vasiliev, 1996,

p. 138), including:

■ Moments. Providing times of events

in geographic space. When did crime

incidents occur and where?

■ Duration. How long did an event or

process continue in a specific space?

For example, how long did a crime rate

remain above or below a certain level

in a particular area? How long did a

hot spot (an area of high crime) persist?

■ Structured time. Space standardized

by time (for example, shift-based

patrol areas, precincts, and posts).

■ Distance as time. We often express

distance as time. “How far is it?”

“About 20 minutes.” More to the

point, perhaps, is concern with

response times. In practice, a fixed,

maximum permissible response time

corresponds to the maximum distance

feasible for patrol units to drive.

Another application would be an

investigation to see whether a suspect

could have traveled from the last place

he was seen to the location of the

crime within a certain time period.

Specialized activities, such as policing,

have their own unique perspective on

time and space; thus, the elements of

Vasiliev’s typology will vary in their relevance from time to time and place to place. 

There is no question that time is an

important element in crime mapping

owing to the time-structured way in

which things are organized in police

departments—by shifts. Patrol area

boundaries may differ by shift, commanders may call for maps of crime by shift,

and resources may need to be allocated

differently by shift. Maps may need to be

prepared on a weekly, monthly, quarterly,

or annual basis to illustrate trends. Timebased maps may be further refined temporally by adding the shift dimension. Crime

data could be mapped vertically, in effect

stacking (merging) maps on top of each

11

Mapping Crime: Principle and Practice

Chapter 1
Context and Concepts

other, using different symbols for different

time periods. Alternatively, a different map

could be prepared for each time period. All

these modifications can be automated by

using GIS.

The importance of selecting appropriate

time periods for mapping cannot be

overemphasized. For example, a map 

covering a month may mask noteworthy

week-by-week variations. Or weekly

maps could hide day-to-day changes.

Mapping intervals selected for administrative convenience may not be the best for

analytical purposes. For example, the calendar week may be best for police department convenience, but local events, such

as an industrial holiday, a sporting event,

a plant closure, or some seasonal phenomenon may cut across administrative time

units and may also have relevance to

crime frequencies. Related questions are,

How much time elapses before a map is

out of date? All data are obsolete sooner

or later, but when is sooner? When is

later? These decisions are quite subjective

and call for a “feel” for the data under

review.

Another aspect of mapping crime in time

and space relates to the representation of

change. One of the most crucial questions

asked in police departments is, How has

crime changed in this neighborhood in the

last week or month or year? Maps can

help answer this question by symbolizing

change in several possible ways, such as

by showing crime as a “surface” with

peaks representing high levels of occurrence (gray areas) and valleys low levels

(red areas) (figure 1.8). This approach

borrows from the methodology of the

topographic map, on which the land surface is represented by contour lines, each

12 Chapter 1

Figure 1.8

A representation of the aggravated assault “surface” in part

of Baltimore County, Maryland.

Red and darker shading indicate higher assault densities.

Source: Keith Harries.
joining points of equal elevation. On the

crime surface map, areas of declining

crime can be shaded differently from those

with increases. Crime mappers are limited

only by their imagination when representing time and space in two dimensions or

simulated three dimensions.

As usual, we should keep an open mind.

Some space-time data may be best represented with a “non-map” graphic, or a

combination of map and statistical graphics,

such as precinct bar charts or pie charts

embedded in a map of precincts. Here we

come full circle, back to cartography as art

and science and to the abstraction/detail

tradeoff. Only crime mappers can decide,

probably on the basis of some experimentation, which graphic representations are

best for themselves and for their audiences.

Map projection

What is it?

A fundamental problem confronting mapmakers is that the Earth is round and the

paper we put our maps on is flat. When

we represent the round Earth on the flat

paper, some distortion (perhaps a lot,

depending on how much of the spherical

Earth we are trying to show) is inevitable.

Map projection is so called because it

assumes that we have put a light source

in the middle of a transparent globe (figure

1.9). The shadows (grid) made on a nearby

surface are the projection.

4 Their characteristics will vary according to where the

surface is placed. If the surface touches

the globe, there will be no distortion at

that point or along that line in the case 

of a cylinder being fitted over the globe,

13

Mapping Crime: Principle and Practice

Chapter 1

Figure 1.9

Diagrams showing cylindrical

and conical projections.

Shadows of the globe’s grid

lines on wraparound paper; 

a cylindrical projection results

(top). Construction of a 

conic projection (middle 

and bottom).

Source: H.J. Blij, Human

Geography: Culture, Society,

and Space, Fifth Edition. 

New York, NY: John Wiley &

Sons, Inc., ©1996, Figures R7

and R8, pages R6 and R7.

Reprinted by permission of

John Wiley & Sons, Inc.
Context and Concepts

touching along the Equator. Away from

the point or line of contact, distortion

increases. Among the most common 

projections are the cylindrical (already

described) and the conical, for which a

cone is fitted over the globe, like a hat,

with the top of the cone over the pole (see

figure 1.9). The cylinder or the cone is cut

and flattened to create the map. The cylindrical projection tends to have much more

distortion at high latitudes (closer to the

poles) compared with the conical. 

The better known projections include the

venerable Mercator 5 (useful for navigation), the Albers conical equal-area 6

, 

and the Lambert conformal conic 7 (the

last two are frequently used for U.S.

maps). Another well-known format is 

the Robinson, now the default world 

map projection used by the National

Geographic Society. Its advantage is that it

minimizes high-latitude distortion of areas

compared with most other cylindrical projections. U.S. States are typically represented by either the Lambert conformal

conic or the transverse 8 Mercator, depending on the size and shape of the State. For

example, Dent (1990, pp. 72–73) noted

that for Tennessee a conical equal-area

projection would be appropriate, with its

standard parallel (the line of latitude

where the projection cone touches the

State) running through the east-west axis

of the State. Projections are a highly technical branch of cartography, and readers

who want to learn more are referred to

standard texts in cartography such as

Campbell (1993), Dent (1990), and

Robinson et al. (1984).

Why we don’t need to worry

Map projections are vitally important for

cartographers concerned with representing

large areas of the Earth’s surface owing 

to the distortion problem and the myriad

choices and compromises available in 

various projections and their numerous

specialized, modified forms. But crime

analysts do not need to be overly concerned with map projections because

police jurisdictions are small enough so

that map projection (or Earth curvature) is

not a significant issue. However, there is

the possibility that analysts will deal with

maps with different projections and that

those maps will not fit properly when

brought together. Streets and boundaries

would be misaligned and structures misplaced. However, this misalignment can

also occur for reasons unconnected with

projection, as explained below. Although

crime analysts do not need to worry about

projections per se, a related issue, coordinate systems, generally needs to be given

more attention because the analyst probably will encounter incompatible coordinate

systems. 

What are the differences between projections and coordinate systems? Projections

determine how the latitude and longitude

grid of the Earth is represented on flat

paper. Coordinate systems provide the x-y

reference system to describe locations in

two-dimensional space. For example, 

latitude and longitude together are a coordinate system based on angular measurements on the Earth’s sphere. But there 

are other ways of referring to points. For

instance, all measurements could be based

14 Chapter 1
on distances in meters and compass directions with respect to city hall. That would

also be a coordinate system. Distances in

feet and directions could be based on the

police chief’s office as a reference point.

The following discussion provides some

details on commonly used coordinate 

systems.

Coordinate systems

What are they?

Coordinate systems allow users to refer to

points in two- or three-dimensional space.

You may have heard of Cartesian geometry, named for the 17th-century French

mathematician Descartes, the founder of

analytic geometry and the Cartesian coordinate system. In two dimensions, we

usually refer to two principal axes, the x

(horizontal) and y (vertical). If necessary,

we add the z axis for the third dimension.

Points are located by referring to their

position on the scales of the x and y (and

z) coordinates. Diagrams usually known

as scatter diagrams, or scatter plots (figure

1.10), are based on Cartesian coordinates,

with their origin in the lower left corner.

Things get a bit more complicated when

the coordinate system is applied to the

spherical shape of the Earth. 

Latitude/Longitude

For the Earth’s sphere, angular measurements must be added to the x-y coordinate system. Latitude angles are

measured from the center of the Earth

between the Equator and poles, 90

degrees north and south, with the Equator

as 0 degrees and each pole 90 degrees.

Longitude angles are also measured from

the center of the Earth, 180 degrees east

and west of the Prime Meridian running

through the Royal Naval Observatory in

Greenwich, England,9 a location fixed by

international agreement in 1884. So all of

the United States is described in degrees

north latitude and west longitude. For

example, New Orleans is located at

approximately 30 degrees north latitude

and 90 degrees west longitude. Latitude

lines are also known as parallels because

they are, in fact, parallel to one another,

and longitude lines are called meridians, as

in “Prime Meridian.” State boundaries west

of the Mississippi River are predominantly

15

Mapping Crime: Principle and Practice

Chapter 1

Figure 1.10

A scatter diagram showing the

relationship between per capita

income and median value of

owner-occupied homes by 

census tract in Orange County,

California, that illustrates the

use of x-y coordinates.

Source: Keith Harries.
Context and Concepts

made up of segments of meridians and

parallels. For example, the longer western

border of Oklahoma is a segment of the

100th meridian.

State Plane and Universal

Transverse Mercator

As noted previously, appropriate map projections have been adopted for each State,

yielding “Earth” projections with coordinates based on latitude and longitude, 

the universal reference system. But these

“latitude/longitude” references, as they

will be referred to, are quite cumbersome,

given that they are in degrees, minutes,

and seconds.10 Two principal alternative

coordinate systems are found in addition

to latitude/longitude: the State Plane

Coordinate System and the Universal

Transverse Mercator (UTM).

The State Plane Coordinate System was

devised for greater user convenience, with

a rectangular grid superimposed over the

latitude/longitude graticule, producing

State plane coordinates expressed in

meters, yards, or feet. In effect, this system assumes that the individual States 

are flat so they can be described by plane

geometry rather than the spherical grid.

For local applications, this use of plane

geometry is acceptable because error due

to failure to take Earth curvature into

account is not significant over relatively

small areas such as police jurisdictions.

Large States are divided into zones with

separate grids for each to avoid the distortion problem. Texas, for example, is divided into the North, North-Central, Central,

South-Central, and South zones; Louisiana

into North, South, and Coastal. Typically,

the origin, or zero point, for a State plane

system is placed in the southwest corner,

just like the scatter plot shown in figure

1.10, to avoid the inconvenient possibility

of having to express coordinates in negative numbers. The origin is also placed

outside the study area for the same reason.

The UTM system is used to refer to most

of the world, excluding only polar regions,

and consists of 60 zones, north-south,

each 6 degrees of longitude wide. Each

zone has a central meridian, and origins

for each zone are located 500,000 meters

west of the central meridian. A sample

location in Texas (the capitol dome in

Austin) is shown in figure 1.11. This

example specifies that the dome is

621,161 meters east of the central meridian of zone 14 and 3,349,894 meters

north of the Equator, the latitude of origin.

The acronym NAD will appear in references to the State plane and UTM coordinate systems. NAD stands for North

American Datum, a reference system that

was based at a Kansas ranch in 1927.

Demands for greater accuracy and more

accurate surveying made possible by

satellites led to a new NAD in 1983,

hence the reference in figure 1.11 to NAD

83 UTM coordinates. 

Why we do need to worry

Crime mappers using computerized data

from different sources may run into a

problem resulting from different data sets

being digitized (assigned their x-y coordinates) in, or converted to, incompatible

coordinate systems or even incompatible

projections. The most frequent conflict is

likely to be between latitude/longitude 

and State plane coordinates owing to the

16 Chapter 1
likelihood that locally developed data (often

in State plane coordinates) will be mixed

with data from more general sources,

probably expressed in latitude/longitude.

We saw that New Orleans is referenced as

30 degrees north latitude and 90 degrees

west longitude in the latitude/longitude

system. But if we refer to it using the

State plane system, it is in the Louisiana

South Zone, with coordinates 3,549,191

feet east of the origin and 592,810 feet

north of the origin. Clearly, if we try to

put the State plane data on a map set up

for latitude/longitude, ugly things will

happen. (What usually happens in a GIS

is that the map goes blank.11) 

Data sets placed together on a map should

have compatible projections and compatible coordinate systems. Fortunately, GIS

software permits conversion from one 

projection to another and from one coordinate system to another, so the problem, if

it does arise, is reasonably easy to fix. But

if incompatibilities are not recognized at

the outset, they can be quite frustrating.

Positive action to check the projection and

coordinate properties of a new data set is

recommended because the coordinate 

system may not be apparent initially.

Map elements: The

usual bits and pieces

Generally, maps have the following 

elements that help provide consistency

and comprehensibility for readers.

■ A title (or caption) to describe the

map.

■ A legend to interpret the content of

the map, such as the symbols and colors.

■ A scale to translate distance on the

map to distance on the ground.

■ Orientation12 to show compass 

direction. 

However, a review of maps in cartography

texts and elsewhere reveals the inconvenient fact that these conventions are often

overlooked. Context should dictate whether

some or all of these elements are included. 

17

Mapping Crime: Principle and Practice

Chapter 1

Figure 1.11

An example of a Universal

Transverse Mercator (UTM)

location. 

Source: Peter H. Dana, The

Geographer’s Craft Project,

Department of Geography,

University of Texas at Austin.

Reproduced by permission. 

Visit Dana’s Web site dealing

with coordinate systems:

http://www.utexas.edu/depts/

grg/gcraft/notes/coordsys/

coordsys.html.
Context and Concepts

For example, in a situation in which maps

of the same jurisdiction, or parts of it, are

produced and distributed to the same

audience on a repetitive basis, a label

telling readers the area would be a waste

of ink. But if the map were intended for

wider distribution to audiences that might

not know what they were looking at, a

caption or heading would be appropriate.

Similarly, scale may be redundant when

the users of the map are educated to the

spatial relationships on the map, often

through years of field experience.

Orientation, too, is unlikely to be critical

in locally used crime maps, for which

north is almost always “up.” It may be

worth noting that Minard’s map of

Napoleon’s army (see figure 1.5) has no

orientation, and if you want to be picky, 

it has no legend per se.

Indeed, a legend is perhaps the only somewhat (but not entirely) indispensable map

element. Readers need to be absolutely

sure what map data mean, and the legend

is the only reliable guide to this information. Some maps may be so simple that 

a legend is not necessary. An example

would be a map showing points, each of

which represents a residential burglary.

The heading or caption of the map (such

as, “Locations of residential burglaries in

St. Louis, September 2000.”) can contain

the necessary information and override

the need for a legend. 

This discussion may imply that one can

be slapdash about map elements, but that

implication is not intended. Careful consideration should be given to whether a particular element should be included; if an

element is included, it must contain complete and accurate information. (For further elaboration, see “Map design” section

in chapter 2.)

Types of map 

information

Maps can provide a rich variety of information, including but not limited to location, distance, and direction as well as

pattern for maps displaying point or area

data. Each type of data means different

things to different users. 

■ Location is arguably the most important of all the types of information to

be represented on, or gleaned from, a

map from the perspective of a crime

analyst. Where things have happened,

or may happen in the future, is the

most sought after and potentially useful piece of information because it has

so many implications for investigators

and for the allocation of patrol and

community resources, in addition to

utility in the realms of planning and

politics.

■ Distance is not much use as an

abstract piece of information. It comes

to life when translated into some kind

of relationship: How far did the victim

live from the place where she was

robbed? What is the maximum distance police cars can travel within a

specific urban environment to provide

acceptable response times? How far

could a suspect have gone in a particular time period?

■ Direction is most useful when considered in conjunction with distance,

although it is not typically an important piece of map information in crime

18 Chapter 1
analysis unless it relates to other relevant processes or conditions. It is generally used in a broadly descriptive

context, such as “the hot spot of burglaries is spreading to the west,” or

“serial robberies are moving southeast,” or “the east side is becoming 

a high-crime area.” In the example

shown in figure 1.12, serial robbers

were found to have a tendency to

migrate south from Baltimore along 

the major highways. 

■ Pattern is an especially useful concept

in crime analysis, as so much of what

crime analysts do involves describing

or analyzing the pattern of crime

occurrences. Pattern can be a powerful

investigative tool because the way

points are arranged may tell us something about the process driving that

arrangement. Patterns are usually classified as random, uniform, clustered,

or dispersed. In a random arrangement, points are just as likely to be at

any place on the map as at any other.

Points are distributed haphazardly

around the map. A uniform distribution

has points that are equally spaced.

Alternatively, we can say that in a uniform distribution the distance between

neighboring points is maximized. In a

clustered pattern, points are clumped

together with substantial empty areas.

It is tempting to assume that the nonrandom distributions (uniform and clustered)

automatically mean that some interesting

underlying process is at work, providing

useful information about crime. This may

or may not be true. For example, burglaries show up in a cluster, suggesting a hot

spot. But further investigation shows that

the cluster corresponds to a neighborhood

with a dense population, so the high 

frequency is no more than an expression

of the geography of risk. The terms

describing the types of patterns are 

subject to some semantic confusion. For

example, what does dispersed mean? 

A dispersed pattern could be random or

uniform. Is “less dispersed” the same as

“clustered”? Various indexes have been

developed to measure regularity, randomness, and dispersion. For additional 

reading, see, for example, Taylor (1977,

chapter 4) and Hammond and McCullagh

(1974, chapter 2).

Line data (for networks, for example) 

and both discrete and continuous areal

distributions are additional types of data.

19

Mapping Crime: Principle and Practice

Chapter 1

Figure 1.12

A map of selected robberies in

Howard County, Maryland, concentrating along the U.S. 29, U.S.

1, and I–95 highway corridors.

The Baltimore-Washington area

Regional Crime Analysis Program

has used maps like this to help

apprehend serial robbers who

cross county lines. For a full

account of this process, see

Mishra, 1999.

Source: Keith Harries.
Context and Concepts

■ Line data. Linear features or processes can be abstracted on maps. The

Minard map (see figure 1.5) did this

by symbolizing the flow of troops to

Moscow and back. The street maps

used to map crime also contain line

data that show points on streets, indicating the linear arrangement of incidents. A map connecting places where

vehicles are stolen to the places where

they are recovered is prepared with

lines connecting the places. Or a line

map might connect victim addresses to 

suspect addresses. Traffic flow can be

shown with lines proportional in thickness to the flow (again like Minard’s

map in figure 1.5). 

■ Discrete distributions. When point

data are combined within unit areas

such as precincts, patrol areas, census

tracts, or neighborhoods, each area is

separated from the others; it is “discrete.” Mapping by discrete areas can

be used to reorganize the point data

into a context that may have more

meaning for a specific purpose. For

example, commanders may want to

see the distribution of drug offenses by

patrol beat to decide how workloads

should be assigned. This could be

measured by density, which expresses

how often something happens within

an area. A common application is population per square mile, for example.

Density also is used increasingly 

frequently to describe crimes, and population density data can provide additional explanation of the risk or rate

concepts in public forums. Graphic representations of this general type, mapping data by administrative or political

areas, are known as choropleth13

maps. (A more detailed explanation is

given in chapter 2.)

■ Continuous distributions are used

less in crime analysis than discrete 

distributions, but they can be useful

and are finding more frequent application in conjunction with, for example,

commonly used software such as

ArcView® Spatial Analyst. Continuous

distributions are phenomena found in

nature, such as the shape of the land

(topography), temperature, and atmospheric pressure. All places on Earth

(above and below sea level) have

topography and temperature, and all

places above sea level (and a few on

dry land below sea level) have atmospheric pressure. Thus it makes no

sense to represent these conditions on

maps divided into areas such as counties

or cities, except for reference purposes.

What does this have to do with crime

mapping? It is sometimes useful to

assume that crime can be represented

as a continuous distribution to prepare

a generalized statistical surface representing crime density. This can provide

a “smoother” picture of crime that

can be enhanced by adding threedimensional effects (figures 1.13 and

1.14). This implies an acceptance of

the tradeoff between loss of detailed

locational information from the point

map and the smoothed, generalized

picture provided by the quasi-continuous presentation. This smoothed 

version may have the advantage of

better legibility than the original detail.

Another advantage of a surface

smoothed across jurisdictions is that it

may vividly illustrate that political

20 Chapter 1
boundaries have little or no meaning

for criminals.

Scale

Maps are miniature representations of part

of reality. Scale tells us how miniature

they are. Scale is commonly expressed as

a ratio, in words, or as a bar graph located

somewhere in the map frame. A ratio

states the scale as a unit of map distance

compared with distance on the ground.

This is referred to as the representative

fraction (RF). Thus an RF of 1:10,000

means that 1 unit of linear measurement

on the map represents 10,000 of those

units on the ground. Units are interchangeable; for a 1:10,000 map, 1 inch

on the map equals 10,000 inches on the

ground, 1 centimeter on the map equals

10,000 centimeters on the ground. 

Scale terminology can be confusing. For

example, large-scale maps and aerial 

photographs used by local governments

(and quite likely to be used by crime 

analysts) are often at a scale of 1:2,400.

If expressed in inches and feet, this is

21

Mapping Crime: Principle and Practice

Chapter 1

Figure 1.13

Early (1976) three-dimensional

maps of Tulsa, Oklahoma, using

the SYMVU program. The robbery

rate is based on the population

(top) and number of persons per

dwelling unit (bottom). The bottom map illustrates the point that

the denominator in crime rates

does not have to be population.

Source: Harries, 1978, figures 43

and 44.

Figure 1.14

A contemporary threedimensional map of

Redlands, California. The

vertical dimension portrays the relative risk of

crime across the city.

Source: Redlands Police

Department. Reproduced

by permission.
Context and Concepts

equivalent to 1 inch equaling 200 feet.

Hence users often refer to the maps simply as “200 scale.”

Large scale or small scale?

The distinction between large scale and

small scale is also a source of confusion,

but there is a simple rule to help us understand. Look at the representative fraction.

If it is a large fraction, the map scale is

large, and vice versa. For example, I open

my National Geographic Atlas of the

World and flip through it until I come to a

map of the world. The scale is expressed

in words as follows: “Scale 1:66,300,000

at the Equator.” This is extremely small

scale, as 1/66,300,000th of

something is not much. A

few pages farther, I come to

a map of the upper midwestern States of the United

States. Its scale is expressed

as “1:2,278,000”—a fraction 29 times larger than

that for the world map. As scales get larger and larger, we move from the realm of

“maps” to what we customarily refer to as

“plans,” such as 1:20, where 1 unit on

the map (plan) equals 20 units on the

ground or the floor plan. These very largescale renderings are the domain of the

architect or engineer rather than the 

cartographer.

Scale has implications for the interpretation and meaning of maps. Implicit in the

concept of scale is the now-familiar tradeoff between abstraction and detail. Small

scale implies more abstraction, large scale

less. Evidence from cognitive psychology

cited by MacEachren (1995) suggests the

importance of progressing from small scale

to large scale when presenting maps of

different areas, the principle of globallocal precedence. In other words, if you

were to prepare maps for the entire jurisdiction and also for a small part of it, the

best mode of presentation would put the

smaller scale map (the entire jurisdiction,

perhaps in the form of a satellite image)

first. The smaller area (larger scale) would

follow this.

Another implication of scale is that crime

data will look different at different scales,

such as citywide and beat levels. The

same data will appear to be more spread

out (less dense) at the scale of the beat

and more crowded (more dense) at the

citywide scale. But in reality densities

(crimes per unit area) are the same on

both maps. What has changed is scale.

Scale also has implications for data collection. If maps are to be large scale, detailed

data collection is appropriate. But smallscale maps are incapable of representing

fine detail, so if the only scale available

for a specific purpose is small, collecting

data at the micro level is pointless. The

detail will be lost on a map incapable of

showing it. The converse is also true.

Gathering data at the ZIP Code level will

be too coarse a scale on a map showing

street addresses.

22 Chapter 1

Rules of Thumb for Map Scale

■ Small-scale maps show large areas.

■ Large-scale maps show small areas.
Maps of crime:

Thematic maps

What is a thematic map? Quite simply, as

the label suggests, it is a map of a theme

or topic. Thematic maps have almost infinite variety and include most of the maps

in the media showing, for example, the

spread of fire ants, the status of sales

taxes by State, or world population density. Thematic maps are like a comprehensive toolkit—we can select a topic and

then choose from many possible ways of

converting the data into a legible map that

effectively communicates with the intended audience. Thematic maps may be

quantitative or qualitative. 

■ Quantitative maps portray numerical

information, such as numbers of

crimes in an area or crime rates. 

■ Qualitative maps show nonnumerical

data like land use types or victim/

offender characteristics, such as male

or female, juvenile or adult.

Crime analysts use both quantitative and

qualitative maps. Thematic maps can

include four kinds of measurement data:

nominal, ordinal, ratio, and interval. (For

a more detailed explanation, see any basic

statistics textbook, such as Burt and

Barber, 1996.)

■ Nominal measurement names or

labels items in unordered categories,

such as race. If a map shows homicide

victims by race, it is a qualitative thematic map. Mapping by race, age

group, or marital status puts labels 

on groups without ranking them as 

higher or lower or better or worse.

(Quantitative information can also be

inferred from this type of map. For

example, the number of incidents

affecting racial groups by areas can be

counted, thus combining qualitative

and quantitative interpretations. Types

of measurements are often mixed on

maps.)

■ Ordinal measurement classifies incidents, victim or offender characteristics, or some other attributes (perhaps

areas) according to rank. Thus patrol

areas or precincts might be ranked

according to their crime rates, their

incidence of complaints, or the average

seniority of officers. This involves only

sorting and evaluating the data according to their relative values so that subjects can be ranked. How much the

subjects differ is not considered. Thus

we can put qualitative characteristics

on an ordinal scale, such as a hierarchy of police areas based on size, with

districts above precincts, which are in

turn above patrol beats. 

■ Ratio scales, such as distance in inches,

feet, yards, millimeters, meters, and so

forth, start at zero and continue indefinitely. Zero means there is none of it

and 20 means there is twice as much

as 10. For example, the homicide rate

is 3 per 10,000 persons in the city.

Crime analysts will use nominal, ordinal, and ratio scales for these data but

are very unlikely to use the fourth kind

of measurement, interval. 

■ Interval scales show values but 

cannot show ratios between values.

Temperature is a good example. We

can measure it, but we cannot say that

80 degrees is twice as warm as 40

degrees, since the starting points of

23

Mapping Crime: Principle and Practice

Chapter 1
Context and Concepts

both the Fahrenheit and Celsius scales

are arbitrary—that is, they are not true

zeros. A possible exception to the

assertion that crime analysts will not

use interval scales could be seriousness

weighting. (See Wolfgang et al., 1985a

and 1985b, for more on this topic.)

Thematic maps come in considerable variety and will be examined in more detail in

chapter 2. Each type represents some kind

of data best. Information with addresslevel detail calls for one kind of thematic

map, whereas data measured only at the

neighborhood, precinct, or census tract

level require a different approach.

Examples of various ways in which thematic maps can be designed are contained

in the following categorization of thematic

maps:

■ Statistical maps use proportional

symbols, pie charts, or histograms to

visualize the quantitative aspects of

the data. Typically, the statistical symbols are placed in each subdivision on

the map, such as patrol areas, census

tracts, neighborhoods, or wards. Such

maps can be quite difficult to read if

they contain a large amount of detail,

particularly when many geographic

subdivisions and several attributes of

the information are being mapped.

Nominal data, such as the race of victims as proportions in precinct-based

pie charts, can be represented on a 

statistical map. 

■ Point (pin) maps use points to represent individual incidents or specific

numbers, such as when five incidents

equal one point. (Aggregating multiple

incidents to single points would be

done only on a small-scale map.) A

map showing locations of drug markets by types of drugs prevalent in

each is an example of a point map

with nominal scale data. Point maps

are probably the most frequently used

maps in policing, as they can show

incident locations quite precisely if

address-level data are used.

■ Choropleth maps show discrete distributions for particular areas such as

beats, precincts, districts, counties, 

or census blocks. Although point data 

can give us the best detail in terms of

where events happen, information may

be needed for areas in summary form

that has meaning in terms of planning,

management, investigation, or politics.

Note that point data and choropleth

representations can both be put on the

same map, if it is appropriate and the

result is not a garbled mess. For example, burglary (point) data could be put

over neighborhood boundaries (choropleth data) or any areas representing

police geography. Also, choropleth

maps can be given a three-dimensional

appearance by making each area into 

a raised block, with the height of the

block representing the relevant data

value.

■ Isoline is derived from “iso,” the

Greek prefix for equal, and refers to

maps with lines that join points of

equal value. Physical geography is

replete with isoline maps that use the

following: isobars (equal barometric

pressure), isohyets (equal rainfall),

isotherms (equal temperature), isobaths (equal depth), and, in a rare

departure from use of the iso prefix,

24 Chapter 1
contour lines to join points of equal

elevation. The form most likely to be

used in crime analysis is the isopleth

(equal crowd), in which data for areas,

such as crimes per neighborhood or

population density, are calculated and

used as control points to determine

where the isolines will be drawn.14

(See Curtis, 1974, for an example of

an isopleth map of homicide, rape, and

assault in Boston.)

■ Surface maps can be regarded conceptually as a special case of an isoline

presentation. Such maps add a threedimensional effect by fitting a raised

surface to data values. Typically, an

arbitrary grid is placed over the map

and the number of incidents per grid

cell are counted. These counts form the

basis for what is, in effect, an isopleth

map that is given its third, or Z 

(vertical), dimension derived from 

the isoline values. The resulting map 

is rendered as if it were being viewed

from an oblique angle, say 45 degrees.

(If it were to be viewed from overhead,

like a normal map, the surface would

be lost and the map would appear to

be a flat contour map.) Such continuous surface maps can make a powerful

visual impact, but they have dual disadvantages in that data values are

hard to read on the map and detail

behind data peaks is lost (see figures

1.13 and 1.14).

■ Linear maps show streets and highways as well as flows using linear

symbols, such as lines proportional 

in thickness to represent flows. Apart

from base maps of streets and highways, crime mappers use linear maps

infrequently—the most common application is vehicle theft investigation

showing connections between the

place of theft and place of recovery.

Data, maps, 

and patterns 

The stage is set. We have a truckload of

data, computers, software, and printers.

Provided our data have been gathered in a

form that permits computer mapping (or

have been converted to such a format; 

see chapter 4), we are at least technically

ready. It should be noted at this point that

computer mapping is not “plug and play”

but is more akin to word processing—the

data have to be entered and sentences

(read “maps”) composed. Similarly, we

will not be able to do computer mapping

until we have data in a format that the

program can understand. Also, many

choices will have to be made. Automated

mapping is automated only up to a point.

(When you put your car on cruise control,

someone still has to steer!)

Before we plug it all in and start mapping,

it might be helpful to pause and think

about the reasons underlying the patterns

we observe and map. Those patterns must

be generated by specific conditions and

processes, and theories can be employed

to help us understand them.

Each type of crime tends to be influenced

by different conditions. For example,

shoplifting is the outcome of circumstances different from those that produce

homicide. Even within crime types, there

are qualitative differences in circumstances. For example, a drug-related

homicide may be the result of a conflict

25

Mapping Crime: Principle and Practice

Chapter 1
Context and Concepts

over turf or unpaid debts, whereas a 

domestic homicide may be the product of

long-simmering animosities between 

partners. 

Crimes may have distinctive geographic

patterns for two underlying reasons that

often overlap:

■ First, crimes must have victims, and

those victims (or their property) have

definite geographic coordinates at 

any given moment, although these

coordinates can shift, as in the case 

of vehicles. 

■ Second, some areas in cities, suburbs,

or rural areas have persistently high

rates of crime, so that for certain

neighborhoods there is a rather permanent expectation that crime is a major

social problem. For example, Lander’s

(1954) research on Baltimore revealed

high rates of juvenile delinquency to

the east and west of downtown from

1939 to 1942. Some 60 years later,

the pattern has changed a little but is

basically the same.

A broad-based discussion of the causes of

crime is beyond the scope of this guide,

and the reader is referred to the substantial literature of criminology for guidance.

However, we can consider issues with

more obvious geographic implications,

and we can do this by moving along a

continuum of scale from the macro to the

micro level. 

On the macro scale, interpreted here to

mean national or regional, geographic

variation is apparent for some crimes,

notably homicide, in the United States.

Although the pattern has decayed somewhat in recent decades, a stream of

research has addressed what has been

called by some the southern violence construct (SVC), the tendency for high rates

of homicide to be concentrated in the

South. Similar regional variations are seen

in other countries. In India, for example,

high homicide rates are seen in the densely populated northern states. 

On the intermediate scale, we see variations in crime rates among cities, although

much of the apparent variation can be

explained by boundary effects. In other

words, “underbounded” central cities

(where the urbanized area spills over

beyond the city limits) tend to have high

rates, since their territories exclude lowcrime suburbs. Conversely, “overbounded”

cities (such as Oklahoma City) tend to

have low rates. However, by no means

are all explanations of rate variation 

necessarily found in boundary anomalies.

Cities differ in social structure, traditions,

mores, the strength of various social institutions, and other conditions relevant to

potential criminality. These include economic conditions, the impact of gangs,

and gun and drug trafficking. The wide

variation in homicide rates among cities is

represented by figure 1.15, which also

reinforces the point that similar numbers

of incidents may yield vastly different

rates. (For an interesting example of

interurban comparisons examining multiple factors, including gangs, guns, and

drugs, see Lattimore et al., 1997.)

On the micro or intraurban scale, a broad

array of environmental factors must be

taken into account if crime patterns are to

be understood. Arguably, the most impor26 Chapter 1
tant general principle is usually known as

distance decay. This is a process that

results from another behavioral axiom,

the principle of least effort, suggesting

that people usually exert the minimum

effort possible to complete tasks of any

kind. Distance decay (see also chapter 6)

is the geographic expression of the principle of least effort. As shown in figure

1.16, the relationship between the number 

of trips and distance is represented by a

line showing that people take many short

trips but few long ones. This principle has

been observed to apply to a broad range

of behaviors, including shopping, health

care, recreation, social visiting, journeying

to work, migration, and last but not least,

journeying to crime. It is possible to create

families of distance-decay curves to represent different classes of movement behavior. For example, shopping trips can be

divided into convenience and comparison

types. Convenience shopping is characterized by many very short trips because

most people will get items such as milk

and bread from the closest possible

source. Comparison shopping occurs when

buyers need big ticket items such as appliances, cars, houses, and college educations. Longer trips in search of more

expensive goods and services are thought

to be worthwhile because price savings

produced by better deals will pay for the

longer distances traveled, at least in theory.

27

Mapping Crime: Principle and Practice

Chapter 1

Figure 1.15

A chart showing mean

annual homicide counts

and rates for 32 U.S. cities,

1985–1994.

Source: Lattimore et al.,

1997, figures 2–4, p. 10.

Figure 1.16

A diagram representing the

relationship between distance and the intensity of

interactions, also known as

the distance-decay concept.

Source: Keith Harries.
Context and Concepts

Similar reasoning might be applied to

criminal movements, although not enough

data have been published to permit much

in the way of generalization. The pioneering work of Frisbie et al. (1977), in

Minneapolis, showed that more than 50

percent of residential burglary suspects

traveled less than half a mile from their

homes to their targets. Commercial burglars went somewhat farther, with some

50 percent of incidents occurring within

0.8 miles. Stranger-to-stranger assaults

had a wider range, with the cumulative

50-percent threshold not accounted for

until a radius of about 1.2 miles from the

offenders’ homes. Commercial robbers also

reached the cumulative 50 percent of incidents at about 1.2 miles. However, a larger proportion of the commercial robbers

traveled longer distances compared with

those who committed the other crimes,

presumably to locate suitable targets and

also to avoid the recognition that may

come with robbing the corner store. Travel

distances tend to reflect population density

and other characteristics of the physical

environment (such as the geography of

opportunities)15, so it is unlikely that distance-decay curves for crimes could ever

apply universally. Nevertheless, the concept of distance decay is still a useful one,

even if curves for specific crimes cannot be

calibrated very accurately.

Although journeys to crime vary among

crime types and with the demographic

characteristics of offenders, targets or 

victims tend to be chosen around the

offender’s home, place of work, or other

often-visited locations. If your home is

burglarized, the chances are that the burglar

is a not-too-distant neighbor. The longestablished prevalence of violence among

intimates is further confirmation of the

idea that most interactions—including

negative ones—occur at short range.

Distance decay is a useful general concept,

but a detailed understanding of the fine

points of local crime patterns demands

detailed local knowledge. Where are the

neighborhoods that are experiencing the

greatest social stress? What are the patterns

of mobility of the population? Who are the

movers and shakers in the drug and gang

scenes, and do their movements affect crime

patterns? What changes are going on? 

Other theoretical 

perspectives

Two of the more compelling theoretical

perspectives deal with routine activities

(Cohen and Felson, 1979; Felson, 

1998) and criminal spatial behavior

(Brantingham and Brantingham, 1984).

In the routine activities interpretation,

crimes are seen as needing three ingredients: a likely offender, a suitable target,

and the absence of a guardian capable of

preventing the criminal act. Guardian is

broadly interpreted to mean anyone capable of discouraging, if only through his or

her mere presence, or interceding in, criminal acts. The mention of guardians begs

discussion of the density paradox. This

refers to the idea that, on the one hand,

high population densities create a high

potential for crime because people and

property are crowded in small spaces.

There are many likely offenders and suitable targets. On the other hand, surveillance

is plentiful, and criminal acts in public

spaces are likely to be observed by others,

who, however unwittingly, take on the

28 Chapter 1
role of guardians. Crime can be prevented

or reduced by making people less likely to

offend (by increasing guilt and fostering

development of the “inner policeman”

who tames criminal impulses), by making

targets less available, and by making

guardians more numerous or effective. The

process of making targets less available in

various ways has become known by the

generic term situational crime prevention

(Clarke, 1992). 

Putting the routine activities approach and

its sibling, situational crime prevention,

into a geographic context involves asking

how each element is distributed in geographic space. Where are the likely

offenders? (What is the geography of the

youthful male population?) Where are the

suitable targets? (What is the geography

of convenience stores, malls, automated

teller machines, poorly illuminated pedestrian areas?) Where are the guardians?

(What is the potential for surveillance,

both formal and informal, of targets or

areas that may contain targets? Where are

the public or quasi-public spaces that lack

surveillance and are ripe for graffiti and

other incivilities?)

The perspective that focuses on criminal

spatial behavior develops a scenario in

which the motivated (potential) criminal

uses cues, or environmental signals, to

assess victims or targets. Cues, or clusters

of cues, and sequences of cues relating to

the social and physical aspects of the

environment are seen as a template that

the offender uses to evaluate victims or

targets. Intimately tied to this process is

the concept of activity space, the area in

which the offender customarily moves

about and that is familiar to him or her

(Brantingham and Brantingham, 1984).

At the micro level of analysis, these concepts are useful in that it is known that

activity spaces vary with demographics.

For example, younger persons tend to

have constricted activity spaces. They do

not usually have the resources to travel

far. Historically, women have had more

geographically limited activity spaces than

men due to the higher probability that

men would work farther from home and

that their jobs would be more likely to

give them greater mobility. This is less

true today but is still valid to some degree. 

Analysts considering crime patterns from

a theoretical perspective might think in

terms of putting the crimes of interest

through a series of “filter” questions. The

most obvious is the question, How important is geography in explaining this pattern? (Is the pattern random, or not? If

not, why not?) Can routine activity theory

or criminal spatial behavior theory help

explain this pattern? Is this pattern normal

or unusual for this area? If the pattern is

an anomaly, why is this? What resources

can be brought to bear to better understand the social and other environmental

dynamics of the area of interest? Analysts

can take their intimate knowledge of the

local environment and develop their own

set of diagnostic questions, which could

be the foundation of an analytic model. 

The basic point of this section is to suggest that a systematic approach to analysis rooted in theory may yield more

consistent results with a deeper level of

explanation. This is not to say that analysts need to be preoccupied with whether

their work is consistent with all the

research ever done but, rather, to advocate a thoughtful research design consistent with some of the more widely

29

Mapping Crime: Principle and Practice

Chapter 1
Context and Concepts

accepted concepts in the field. As noted,

this short explanation cannot do justice to

the rich array of material dealing with 

theory in this realm. Readers who may

wish to follow up should consult Eck and

Weisburd (1995) and the other references

cited previously.

A note on cartograms

Maps that distort geography to emphasize

a specific type of information are called

cartograms to imply a combination of

map and diagram. The media often 

publish maps showing world or U.S. 

population data as cartograms, with the

areas of countries or States proportional to

their populations. Cartograms may also

represent linear data by showing travel

time, for example, rather than physical

distance between places. 

Cartograms have not found widespread

application in crime mapping, although

they could be useful. For example, urban

subdivisions could be shown with their

areas proportional to the number of crime

incidents. The major limitation in using

cartograms for crime data is the lack of

software availability to permit their easy

preparation. Historically, cartograms have

been labor-intensive projects, each needing to be custom drawn. When viewed

from a cost-benefit perspective, the novelty and impact of cartograms for crime data

have not been seen as worth the cost.

Reminder: Information

is inevitably lost in the

process of abstraction

Cartographer Mark Monmonier (1991)

pointed out that the three fundamental

elements of maps—scale, projection, and

symbolization—can each be distorted. In

creating the abstraction called a map, loss

of information is taken for granted. Given

that there will be information loss, the

question is whether we are properly representing the “residual” information left

after the data are reduced to manageable

proportions. As noted earlier in this chapter, our maps may “lie” as a result of sins

of omission or commission. We may forget to do something and get errors as a

result, or we may do something that creates errors—or both. 

Because all abstractions lie in some way,

we come full circle to the awareness of

both art and science in cartography. As

crime mappers, we should maintain a

background awareness that we may make

artistic (design) decisions that obfuscate.

We may make scientific decisions that

misinform. Could our map sidestep a

degree of accuracy that it might otherwise

have achieved? (How should these data

be preprocessed? Should the mean 

or median be used to characterize these

data?) More often than not, only the 

analyst/cartographer knows for sure how

truthfully a map conveys its message, 

so she or he has considerable ethical

responsibility.

A note on the 

maps in this guide

Please note that the publication process

puts some limitations on the quality of 

the maps used as examples in this guide.

While crime analysts are typically able to

produce high-quality maps, often in large

format for display purposes, we are limited

here to small maps that were usually in

30 Chapter 1
larger format when produced. Fortunately,

we are able to produce maps in color,

which helps enliven the visual message

and also helps to convey the various 

concepts involved. Loss of definition

occurs in some cases because the original

has been scanned or resized, or both. In

some cases, only a low-resolution original

was available, yielding a low-resolution

reproduction.

Thus most of the maps seen here are

compromised in some respects and are

unlikely to be the perfect exemplars that

we would prefer. Perhaps “do as I say but

not necessarily as I appear to have done”

would be a fair warning! Ideally, of

course, maps should be clear and crisp

with appropriate shading or symbolization

and legible labels and headings. If that is

not the case here for any of our examples,

please accept our apologies. The original

authors of the maps who have so generously consented to their use here are not

to blame for any shortcomings in their

reproduction or adaptation.

Purists may be shocked by the presentation of so many maps that lack some of

the basic elements normally considered

essential in map design, such as a scale, a

north arrow, or even a legend. Relatively

few maps have what may be called classic

good looks. The maps used here were

often selected for their ability to illustrate

one central point, and strict conformity to

classic design criteria was not seen as a

critical determinant for inclusion. Indeed,

had the strict classical criteria been

enforced, this volume would not exist

because, as noted elsewhere, few maps in

any field go by the book. It would have

been necessary to modify most maps to

make them conform to strict standards,

and this was simply impractical.

Some maps identifying specific neighborhoods in specific cities in sufficient detail

to permit the possible identification of

individual residences have been constructed using hypothetical data or have been

otherwise fictionalized to preserve privacy.

It is not my intent to present accurate renditions of crime patterns in specific cities

but, rather, to illustrate elements of design

and map application. No map reproduced

here should be used as a reliable guide to

actual crime patterns in actual places.

Summary

Chapter 1 has explained:

■ What this guide is about and how

crime mapping fits in the historical

context of mapmaking. 

■ Why cartography is both an art and a

science.

■ Why it is important to balance costs

and benefits when considering map

design and production.

■ That maps can represent information

relating to both time and geographic

space.

■ The meaning and significance of map

projections and coordinate systems.

■ The traditional elements that help 

provide consistency and interpretability

in maps. 

31

Mapping Crime: Principle and Practice

Chapter 1
Context and Concepts

■ The types of information provided by

maps.

■ Measurement systems and their 

relevance to mapping.

■ The meaning of the term “thematic

map.”

■ The ethical responsibilities of crime

mappers.

■ The difficulties associated with the

black and white reproduction of maps

that were originally in color.

■ The importance of thinking about the

causes underlying the patterns that we

map and analyze. 

■ The meaning and possible application

of cartograms in crime mapping. 

■ Why we should realize that we can 

lie with maps just as we can lie with

statistics.

32 Chapter 1

What’s Next in Chapter 2?

■ What crime maps should do and how they should do it.

■ How to choose the right kind of crime map.

■ Types of thematic maps. 

■ Why the data should be explored.

■ How to choose class intervals in numerical data.

■ What is involved in crime map design.

■ How crime map design, abstraction, and legibility are related.

Notes

1. Photographs were not very useful

because they had to be enlarged to an

impractical size to be legible.

2. From the Latin c(h)art(a) and Greek

graph(os), something drawn or written,

hence “chart drawing.”

3. India ink is a mixture of lampblack 

and glue.

4. This grid is also known as a graticule,

a term meaning the spherical pattern of

meridians (north-south longitude lines)

and parallels (east-west latitude lines).

See Campbell, 1993, p. 23.

5. Mercator’s projection, developed by

and named for Gerhardus Mercator

(1512–1594), a Flemish cartographer, is

useful for navigation because a straight

line on the map represents a true direction

on the Earth’s surface.
6. Equal-area projections, as the name

implies, accurately represent area, but not

shape. This type of projection shows area

distributions such as vegetation, in which

the area shown is critical.

7. Conformal projections retain correct

shapes. An added advantage is that, if

shape is retained, so is direction.

8. Transverse Mercator has the projection

cylinder fitted horizontally—i.e., east-west,

rather than tangentially to the Equator or

north-south.

9. Latitude is relatively easy to determine

with reference to “fixed” objects such as

the North Star or the Sun. Longitude, as

noted earlier, poses greater difficulties. It is

known that the 360 degrees of longitude

divided into the 24 hours of the day means

that each hour is equivalent to 15 degrees

of longitude. Thus if the time at a known

point could be maintained on a ship at

sea, longitude could be calculated based

on the time difference as established locally from the occurrence of the noon Sun.

The problem, until John Harrison’s invention of the reliable marine chronometer

in 1761, was that no clock was able to

retain its accuracy under the difficult conditions of a sea voyage. The extraordinary

saga of Harrison’s success is found in

Sobel (1995). (I learned more than I cared

to about this problem on a trip on a 30-foot

sailboat from Honolulu, Hawaii, to Santa

Barbara, California, when the crew forgot

to set the chronometer on leaving Honolulu.

The crew always knew their approximate

latitude by using a sextant but never

knew their longitude. Fortunately, they

kept moving east and eventually bumped

into North America.) 

10. In case inquiring minds want to know,

1 nautical mile, or “knot,” is equivalent to

1 minute of latitude, or 1,852 meters

(6,076.12 feet). One nautical mile is also

equivalent to 1.1507 statute miles (Dent,

1990, p. 40).

11. This happens because a GIS will try to

put both locations on the same map in the

originally specified map units. This may

result in the map changing to extremely

small scale (see explanation of scale in this

chapter) as the GIS tries to make State

plane coordinate values into degrees of

latitude/longitude, placing the new data far,

far away. The GIS may try to show data

for small areas in Brooklyn and what it

reads as Afghanistan or Antarctica on the

same map.

12. The term orientation is derived from

medieval T-in-O maps. The “O” was the

world ocean; the “T” was formed by the

Mediterranean Sea (vertical), the Don

River (left top of the T), and the Nile

River (right top of the T). Paradise in this

style of map was typically at the top, in

the east. Hence the verb to “orient” a map

came to mean adjusting it to its proper

direction in relationship to the Earth. Today,

however, we orient a map so that north is

at the top, which is something of a misnomer (Campbell, 1993, pp. 246–247).

13. From the Greek choros for place and

plethos for fullness or crowding, hence

“area crowd.”

14. Isolines based on continuous data,

such as temperature or topography, are

referred to as isometric lines. Actual

measurements can be made to provide

control points instead of averaging points

over areas.

33

Mapping Crime: Principle and Practice

Chapter 1
Context and Concepts

15. The term “geography of opportunities”

refers to the idea that the world offers

abundant possibilities for crime that may

be more complex than we realize at first

glance, encompassing both qualitative and

quantitative dimensions. For example,

although rich neighborhoods may not

offer more opportunities than poor neighborhoods for, say, property crime, each

opportunity may offer the perpetrator

higher value because the goods stolen

may be worth more.

34 Chapter 1
35

Mapping Crime: Principle and Practice

Chapter 2

Chapter 2: 

What Crime Maps

Do and How They

Do It

What crime maps do

Maps are often thought of solely as display tools. In

fact, maps have a wide-ranging role in the process of

research, analysis, and presentation. Mapping is most

effective when those broad capabilities are recognized

and used to their fullest extent. The map is the end

product of a process that starts with the first-responding

officer’s report that is processed by data entry personnel, entered into a database, and transformed into a

symbol on paper. In this narrow interpretation, a map

is merely a picture or part of a database. But maps

can be useful in other ways. MacEachren (1994) and

MacEachren and Taylor (1994), following DiBiase

(1990), noted the distinction between visual thinking

and visual communication in the use of maps and

graphics (figure 2.1). 

Visual thinking

In visual thinking, the map is used to generate ideas

and hypotheses about the problem under investigation.

By inspecting a map, for example, we may notice a

relationship, or correlation, between environmental

factors that otherwise might have gone unnoticed.

This correlation may be vertical in the sense that we

see connections between different phenomena, such
What Crime Maps Do and How They Do It

36 Chapter 2

as crimes, land uses, and demographics.

Alternatively, we may see a horizontal

relationship in which we recognize a common factor across a particular crime type,

such as graffiti in similar types of crime

locations. Visual thinking is a private activity involving exploration and confirmation. 

In the exploratory phase, maps may be

crude and are not intended for display or

publication. A computer-printed map of

burglary patterns for the most recent week

might be marked with handwritten information provided by investigators or with

other data not in digital form. Information

might be transcribed from a mental map

to a paper map. Another possibility is that

the tools of exploratory spatial data analysis

(ESDA) are used to find anomalies in

data, such as an unexpected cluster of

incidents, that could point to unexpected

relationships.

At this stage the analyst may generate 

a formal hypothesis, or educated guess, 

to explain the process producing the

observed crime pattern. Did the observed

cluster of burglaries pop up by chance? Is

there some recognizable cause? Is a serial

burglar operating in the area? Do officers

in the field have insight to offer? By

developing a hypothesis, the analyst is

in the mainstream of scientific research,

using a venerable methodology—the 

Visual Thinking versus Visual Communication

■ Visual thinking is abstract and internal. Some ideas for putting data

into maps, charts, or other media may never see the light of day.

■ Visual communication is a tangible expression of visual thinking. It is

putting thoughts about data and processes into a format others can

see and understand with minimal effort.

Figure 2.1

The roles of graphics in the

research process: Visual thinking and visual communication. 

Source: DiBiase, 1990.

Reproduced by permission.
so-called (and awkwardly called) 

hypothetic-deductive method. 

Maps and other graphics are integral tools

for exploration and hypothesis testing. Do

preliminary maps confirm the hunch that

a burglary pattern is likely the product of

a repeat offender who is using a bus

route, and apparently a specific bus stop,

to visit a neighborhood and commit his

offenses? If so, the preliminary information will help the hypothesis gel into

something useful.

At the core of this method is a potentially

repetitive process involving: 

■ Development of a hypothesis on the

basis of the best available information

derived from both theory and field

data. 

■ Development of a method for testing

the hypothesis, perhaps involving statistical and graphic testing or modeling. 

■ Analysis of the data.

■ Evaluation of the results.

■ A decision to accept or reject the original hypothesis. 

■ Reevaluation of the original hypothesis, if it was unsatisfactory. It may be

modified to take into account new

knowledge. If so, the process begins

anew. 

The confirmation stage tells the analyst

whether the hypothesis does indeed have

a factual basis that will withstand scrutiny. If it does not, we reevaluate and make

necessary adjustments, perhaps gathering

more information to add depth to what

is already known and to shore up the

hypothesis, which itself may now have

been modified to take new data into

account.

MacEachren (1994) cautions that investigators should realize that maps and other

graphics are prone to error resulting

from their underlying data, inappropriate

design, or even the margin of error 

37

Mapping Crime: Principle and Practice

Chapter 2

What’s Hypothesis Got to Do With It?

Will the typical crime analyst go through the rigmarole of visual thinking

and visual communication—plus the process of hypothesis testing? It’s

not likely, since most analysts work under tough deadlines with inadequate resources. (Just like everyone else!) Also, much of the work is 

prescribed, routine, and repetitive, leaving little flexibility for research. 

So, what’s the point? The formal structure outlined here is an ideal model

for map-related research—a paradigm or modus operandi. Thus it is unlikely

to be replicated often in practice. Like other models, it provides an ideal

guide and enables the analyst to apply whatever parts of the process

can be applied in the time available.
What Crime Maps Do and How They Do It

introduced by the normal process of

abstraction. If possible, the analyst should

not rely on any one data source, whether

it be a map, field observation, or survey, if

other sources can be used to complement

each other.

Visual communication

As we move from visual thinking to visual communication, we go from the private

realm to the public activities of synthesis

and presentation. Synthesis implies merging various types of information—in this

case, geographic information system (GIS)

layers—into a coherent final product.

Although synthesizing is essentially 

scientific, human judgment is at the 

core of this filtering and refining process.

Synthesis is assisted by the ability to find

overlaps (intersections) between layers in a

GIS. But even then decisions have to be

made about what to put in, what to leave

out, and what importance to attach to

each layer. A presentation puts all the relevant pieces together in a map. The map can

be highly persuasive if it provides information germane to the question at hand and is

well designed. As MacEachren (1994, p. 9)

noted, “People believe maps.” 

How crime maps do

what they do

A detailed discussion of how maps communicate through processes of visual

comprehension is beyond the scope of 

this guide. However, a few points are

made here to explain the underlying

process and underscore the idea that people see maps differently due to differences

in, for example, their eyesight, aptitude

for visual comprehension, and prior training. A background problem that goes

largely unrecognized in the community of

mapmakers is that, for some people, maps

have no meaning. They may grasp neither scale nor symbolization. As a result,

they have no sense of distance, relative or

absolute, and are unable to draw meaningful conclusions from a map. 

This problem is, in part, a legacy of the

disappearance (until recently) of geography from school curriculums. But it may

go deeper, seemingly having to do with

gender- and race-specific differences in

personal mobility that, in turn, may hinder the development of spatial experience

and reduce individuals’ abilities to take

advantage of maps as tools. For example,

in the past, women’s traditional roles in

childrearing have limited their mobility,

thus denying them opportunities to learn

geography by directly experiencing places.

Race has had a similar indirect effect

through the mechanisms of discrimination

and depressed economic status. Insofar as

minority groups have experienced disproportionate levels of poverty, their mobility

has been limited and their geographic

learning correspondingly stunted. (See

Montello et al., 1999, for a discussion of

related questions.) While the police are very

geographically aware, in part due to much

field experience, individual members of

the community may not be. An argument

might be made for giving special attention

to maps intended for the community. For

example, digital photos of landmarks

could be embedded in a community map

as visual anchors to show residents how

the map relates to their environment.

38 Chapter 2
All messages, including maps, are laced

with nuance. “The medium is the massage,” wrote McLuhan and Fiore (1967),

arguing that literate people had been 

rendered visually incompetent by an

excessive dependence on text. Since that

famous remark, personal computers have

provided an interactive platform, allowing

what is, in effect, environmental manipulation on the fly. Maps, text, and data

have moved from the realm of the passive

to the active and interactive, encouraging

perception of the map as a tool rather

than as a mere display device. 

Peterson (1995) has outlined several 

theories and models that have been

advanced to explain how visual information is processed:

■ Stage model. Visual information

moves through three memory stages.

The first (iconic) is very short and

deals with initial recognition. The second (short-term visual store) is longer

but has less capacity so complexity

becomes an issue. Moving from iconic

to short-term demands attention. The

information is then sent to long-term

visual memory. Long-term images provide cues to help with recognition of

new visual stimuli.

■ Pattern recognition theory. Iconic

images are converted into something

recognizable through pattern matching.

■ Computational model. This sophisticated three-dimensional model is similar to the process of abstraction in

cartography. (For additional discussion, see Peterson, 1995, chapter 1.)

These theoretical considerations are

reminders that producing a map is only

half the story. We also have to be concerned with how it is interpreted by the

intended audience. The storage of cues

for the interpretation of visual images in

long-term memory means that familiarity

provides a substantial advantage in the

interpretation of maps. We may be oblivious to the fact that our map is extremely

familiar to us but means little or nothing

to those who have no reference points in

their long-term memory or who have had

insufficient time to study and process the

details.

Another way of visualizing the process of

moving a concept from the analyst to the

map user is illustrated in figure 2.2, showing that the cartographer’s and map user’s

realities are both abstractions of reality.

The cartographer creates a cartographic

39

Mapping Crime: Principle and Practice

Chapter 2

Figure 2.2

A model of 

cartographic 

communication. 

Source: Peterson,

1995, figure 1.1, 

p. 5. Adapted 

by permission of

Prentice Hall, Inc.,

Upper Saddle River,

New Jersey.
What Crime Maps Do and How They Do It

abstraction and translates this into a map

that is read by the map user and transferred to the user’s mind.

Choosing a crime map

Chapter 1 characterized thematic maps as

falling into the following broad categories:

statistical, point, choropleth, isoline, surface, and linear. How do we choose the

most appropriate type for mapping crime

and crime-related phenomena? Some decisions jump out at us while others are open

to interpretation. 

For example, if we want to see the precise

locations of burglaries for the last month,

then we use a point map of addresses of

incidents. Or perhaps a city council member has asked the police department for a

map summarizing the number of incidents

of graffiti per structure by city neighborhoods. This calls for a choropleth map,

with neighborhood boundaries making up

the geographic units. Links between victim

and offender residences demand a linear

representation. A generalized picture of

crime risk or incidents is seen best with an

isoline or surface map, and census information depicting the relationship between

poverty and race can be shown using

either a statistical or choropleth map. 

Because of the infinite potential combinations of crime-related conditions that can

be depicted on maps, we can combine

map types to put more information on the

same map. For example, we can combine

nominal and ratio data, such as a choropleth map of drug-related crime by patrol

beats and add the locations of drug markets on the same map. Crime mappers

should be aware of the potential for 

combining thematic map types, provided

that the result is not overloaded with

information—or just plain incomprehensible. An overloaded map will have so

much information that the eye is unable

to take it all in. It will prevent the reader

from discriminating between what is

important and what is not.

Examples of 

thematic maps

Perhaps the best way to get a feel for the

kinds of maps used to display crime data is

to look at examples and to think about why

each type of map was selected. A good place

to start is the Web site of the National

Institute of Justice Crime Mapping Research

Center (http://www.ojp.usdoj.gov/cmrc),

which provides links to police departments

across the United States. Another useful

Web site is maintained by Hunter College in

New York (http://everest.hunter.cuny.edu/

capse/projects/nij/crime.html). (See the

appendix for additional information.)

Thematic maps using point 

symbols: The dot map

When should point symbols be used? The

first prerequisite is that you have locational

detail—information specific to your points,

such as street addresses or coordinates in

latitude/longitude or some other system,

such as State Plane (explained in chapter 1).

The second prerequisite is that the audience needs locational detail. If you have

point data, but the audience wants information summarized by patrol areas or

neighborhoods, then the point data can be

added up, or aggregated, to the areas of

interest. Examples of point, or dot, maps

are shown in figures 2.3 and 2.4.

40 Chapter 2
41

Mapping Crime: Principle and Practice

Chapter 2

Figure 2.3

A point data map 

discriminating among

three crime categories

with different symbols

and colors. 

Source: San Diego,

California, Police

Department.

Reproduced by 

permission.

Figure 2.4

A point data map of

drug arrests using 

different symbols and 

colors. 

Source: San Diego,

California, Police

Department.

Reproduced by 

permission.
What Crime Maps Do and How They Do It

When there are too many points to be

mapped, using point data may result in a

mess of superimposed points that have little or no meaning. This could happen if

calls for service are mapped using addresses in a large city. The point data may need

to be summarized by areas to make the

data legible. Point maps also get too

crowded if long time periods are summarized for more frequent crime categories.

Thus, even though you have reasonably

precise locational information, aggregation

by areas in the form of a choropleth map

may yield a more legible map than the

presentation of each individual point.

Thematic maps using 

statistical symbols

At its most primitive, a statistical map

consists of raw numbers written in the

subdivisions of the map. The advantage is

that the reader can see exactly what the

statistic is. The downside is that maps

designed in this way are difficult to read

quickly. It could be argued that, in effect,

they defeat the purpose of the map, which

is to facilitate visualization of the data.

Admittedly, this form of map does put

data in its geographic context, but in an

inconvenient format. Cartographers argue

that if you want to see only the raw numbers, then a table, not a map, is needed

(see next section, “Thematic maps using

area symbols”).

Statistical symbols commonly take the

form of pie charts, bar charts, graduated

circles, or dots representing incident

counts (dot density) placed in the relevant

map subdivisions (figure 2.5). This allows

multiple variables to be mapped at the

same time. Examples could include bar

charts with bars representing both crime

and poverty or graduated circles like those

in figure 2.6, showing the U.S. House of

Representatives vote on an Omnibus Drug

Bill provision requiring a 7-day waiting

period for the purchase of handguns. At

first glance, the symbols in figure 2.6 look

42 Chapter 2

Figure 2.5

Thematic mapping options

in MapInfo®, a desktop

mapping program.

Source: MapInfo

Corporation, Troy, 

New York.
like pies, but circle segments are all 90

degrees. This is actually a graduated circle

map, in which the area of the 90-degree

segments is proportional to the number of

yes votes (top part of the circle) or no

votes (bottom part of the circle), with the

left side of the circle representing votes by

Democrats, the right by Republicans.1 The

map shows both nominal data (party affiliation and yes/no votes) and quantitative

data (the number of votes), as well as

location of votes by State. Although reading this map takes some effort, it is rich in

information and gives that information a

clear geographic context. 

More typical graduated symbol maps used

in crime analysis applications are shown

in figures 2.7, 2.8, 2.9, and 2.10. Note

that points and proportional circles can be

43

Mapping Crime: Principle and Practice

Chapter 2

Figure 2.6

A graduated circle map

showing a U.S. House of

Representatives vote on

an omnibus drug bill

provision requiring a 

7-day waiting period 

for the purchase of

handguns. 

Source: T. Rabenhorst,

University of Maryland,

Baltimore County,

Maryland. Reproduced

by permission.

Figure 2.7

A graduated circle

map showing aggravated assaults by 

census block group,

Baltimore, Maryland. 

Source: Keith Harries

from Baltimore City,

Maryland, Police

Department.
What Crime Maps Do and How They Do It

44 Chapter 2

Figure 2.8

A graduated circle

map showing convenience store robberies,

Baltimore County,

Maryland.

Source: Philip Canter,

Baltimore County,

Maryland, Police

Department.

Reproduced by 

permission.

Figure 2.9

A graduated circle

map showing 

robberies in Overland

Park, Kansas. 

Source: Susan

Wernicke, Overland

Park, Kansas, Police

Department.

Reproduced by 

permission.
combined if this helps convey the essential information to readers and avoids

overloading the map. Note also that the

size range for symbols is a judgment call.

If the size range is too small, readers will

have difficulty extracting meaning from

the map. Also, some symbols are more

effective than others in conveying the

message. Solid symbols probably work

best in most cases because they engage

the eye more effectively.

A disadvantage of using statistical

symbols on maps is that they may overlap one another and result in an illegible

mess. Map design must take into account

the final size of the map, the scale to be

used, and the possibility of overcrowding.

The use of statistical devices of various

kinds on maps is limited only by the analyst’s imagination. For example, it may be

useful to accompany a map with a scatter

diagram showing a collateral relationship,

such as calls for service by time of day

(chart) and calls for service by location

(map). Mapping software offers numerous

possibilities because the programs usually

can make both charts and maps and 

combine them in layouts in useful ways.

Thematic maps using 

area symbols

When we think of making maps that represent areas, it’s the choropleth map that

usually comes to mind, with administrative or political areas shaded according to

their statistical values, whether they are

frequency counts, averages, or other relevant measures. When is a choropleth map

appropriate? Strictly speaking, mapping

total numbers, such as crime counts,

using choropleth mapping is unacceptable

owing to the misleading impression given

by unequal areas. For example, if the

largest and smallest areas have the same

frequency, they will be shaded the same

on the map, which fosters possible 

misinterpretations based on per capita or

density considerations. However, many

departments overcome this by using a

regular grid for choropleth mapping. This

has the advantage of equalizing areas but

the possible disadvantage that the units of

the grid may not be “natural” local areas.

45

Mapping Crime: Principle and Practice

Chapter 2

Figure 2.10

A graduated symbol

map showing calls for

service in a San Diego

neighborhood. 

Source: San Diego,

California, Police

Department. Reproduced

by permission.
What Crime Maps Do and How They Do It

In other words, the areas exist only on

police department maps and may be difficult to interpret in the field. 

For places with boundaries following the

rectangular land survey, a grid of square

miles (sections) or quarter-square miles

will be substantially visible in the local

street pattern system. This applies to most

areas west of the Appalachian Mountains.

East of the Appalachians, survey systems

were usually based on irregular “metes

and bounds” and do not lend themselves

to grid-based maps, except where cities

have a regular block grid. (See also chapter 4, “Definition in geographic space.”)

Examples of choropleth maps are shown

in figures 2.11 and 2.12.

Choropleth maps are best used for area

averages, such as crime rates, population

density, and percentages, as well as 

nominal-scale information such as land

use. Care is needed in the interpretation 

of all maps, and choropleth maps are no

exception. Take, for instance, a choropleth

46 Chapter 2

Figure 2.11

Choropleth maps showing

residential burglaries in

Baltimore County, Maryland.

Source: Philip Canter,

Baltimore County, Maryland,

Police Department.

Reproduced by permission.
map of a crime rate based on population.

Map values are expressed in terms of

numbers of crimes per population unit.

But what population? Normally, the residential population as enumerated in the

census is implied. What about downtown

business areas with negligible residential

populations? They still have crimes and

the statistical effect is to inflate the crime

rate. Is this realistic? 

One could take this scenario to the

extreme: If small areas are used for crime

rate calculation, we may have areas with

crimes but no resident population, producing

an infinite crime rate! Bear in mind that

the crime rate concept is a loose one and

crime rate maps are only an approximation,

particularly for smaller areas. Although

neither the offenders nor the victims are

necessarily residents of the areas where

the crimes happen, they would nevertheless be represented in crime rate maps. 

Experience has shown that it may be

helpful to add a disclaimer note on some

maps to point out, where appropriate, that

some areas with high crime rates have

small or zero residential populations.

Another form of this disclaimer would

note that rates have not been calculated,

or have been intentionally omitted, for

areas with small or no residential population.

This will have to be handled carefully,

47

Mapping Crime: Principle and Practice

Chapter 2

Figure 2.12

A choropleth map

showing land uses

(choropleth colors) and

auto thefts (proportional circles) in Overland

Park, Kansas.

Source: Susan Wernicke,

Overland Park, Kansas,

Police Department.

Reproduced by 

permission.

Rule of Thumb

Avoid generating choropleth maps of crime rates for small areas like city

blocks because spurious results could be produced for areas where there

are crimes but no residents.
What Crime Maps Do and How They Do It

however, since some readers may conclude that the police department has

something to hide if data are manipulated

in what appears to be a selective way.

Note that choropleth maps can be produced

in a three-dimensional format with the

height of each area proportional to its data

value.2 The advantage of this type of presentation is visual appeal and vividness. The

disadvantages are that it can be difficult to

decipher the actual data value, and that a

tall column will hide other areas, as is the

case in three-dimensional surface maps.

Thematic maps using surfaces

Although crime maps using isolines 

have been around in some form since the

1960s, they have only recently become

widely used.3 This is a result of the availability of algorithms in mapping programs

that perform complex calculations at 

high speed. With the addition of threedimensional capabilities, surface maps

with textured surfaces are now within the

reach of most crime analysts. Such maps

are tempting as they are visually more

appealing than two-dimensional renditions. But the same caveats noted above

apply. Just because a surface map or

three-dimensional rendition can be produced, it does not necessarily follow that

it is the most appropriate or useful form

for visualizing the data. For example, it

may be difficult to add legible landmark

icons or even boundaries to a threedimensional map, depending on factors

such as scale and amplitude, or the degree

of peakedness, of the map, as well as the

angle of view. (See figure 1.14 and chapters 4 and 6 for other examples of threedimensional maps.)

Ultimately, deciding whether to use a surface map involves balancing scientific and

artistic judgment, and in many cases the

decision can be made only through experimentation. Fortunately, maps can be produced rapidly with desktop computers, so

experimentation can and should be a routine part of the mapmaking process.

Thematic maps using 

linear symbols

Flows between points are shown with linear symbols, with their width or thickness

generally proportional to the volume of

the flow (figure 2.13). Maps of this type

had their origins in economic geography,

first showing passenger flows on Irish

railways in the 1830s and, later, commodity flows among nations (Campbell, 1993,

p. 264). These maps can be used in crime

mapping, to show, for example:

■ Links between where vehicles were

stolen, where they were recovered, and

suspects’ addresses.

■ Routes between victims’ and offenders’

home addresses (e.g., Pyle et al.,

1974; Frisbie et al., 1977, p. 88).

■ Passes along streets by patrol cars to

illustrate patrol density.4

■ Traffic density.

Virtually no flow maps have been seen in

the recent literature on crime mapping,

even though such maps are in use in

police departments. Their absence is not

due to lack of data. It may be that the

apparent lack of this type of map in the

literature is due to the absence of readily

48 Chapter 2
available flow-mapping algorithms in the

GIS programs most popular among crime

mappers. While it is unlikely that flow

mapping will ever be a major component

of crime maps, it will be increasingly used

owing to its obvious utility in limited

applications. 

Classifying map 

information

Generally, information on maps is classified in some way; data are not symbolized

individually. For example, all burglaries

are shown with the same symbol on a

point map. It would be absurd to show

each crime with its own symbol. 

In effect, maps contain two levels of

abstraction: 

■ The overall level of detail and the scale

used to present the data.

■ The way data are symbolized, because

there is a continuum from highly

detailed to extremely generalized in the

symbolization process. 

To some extent, the choice of scale controls the level of abstraction of the content

because it is impractical to load a smallscale (large area) map with local detail.

MacEachren (1994, p. 41) argues that for

categorical information, “features that end

up in the same category should be more

similar to one another than features in 

different categories.” 

What does this mean for crime maps? A

map of drug offenses might group related

drug categories together. Generically related robberies could be put together in the

same category and symbolized the same

way on a general crime or violent crime

map. If a map were specific to robberies,

however, symbolization might be separated into commercial and street or weapon

type or time of day. This type of adjustment is intuitive and naturally occurs in

the crime context where data are typically

sorted into categories as part of normal

49

Mapping Crime: Principle and Practice

Chapter 2

Figure 2.13

A thematic map using

linear symbols that

shows numbers of 

residential burglaries,

arrests, and suspect

movements, Akron,

Ohio. 

Source: Pyle et al.,

1974, figure 42, 

p. 167. Copyright,

1974, University 

of Chicago.
What Crime Maps Do and How They Do It

50 Chapter 2

How Many Classes in a Map?

Use no more than six—and not less than four—classes, or shading levels,

of data in a choropleth map.

processing. But the situation becomes

more intricate when moving from nominal

and ordinal data to ratio-type data.

It is less obvious how to classify numerical

data when several alternatives present

themselves. Common mapping software

packages offer options, including a default,

for grouping numerical data in thematic

maps but rarely explain how to choose

among these approaches. Dividing up the

data range in a way that best represents 

it involves the abstraction issue again. 

Total abstraction would be represented by

the use of one shade for all areas on the

map. This says that there are data, but little or no specific information is supplied

about them. At the other extreme, each

area would have its own shade, and if city

blocks were shown, the map would have

thousands of shades. Obviously, neither of

these alternatives is useful, and the solution lies somewhere between. 

Greater accuracy dictates the use of more

classes of data, although readers pay a

price for this in terms of comprehension as

the map moves along the continuum of

abstraction toward reality and complexity.

The underlying question is, What is this

map being used for? MacEachren (1994,

pp. 42–43) suggests that if we are in the

visual thinking stages of exploration and

confirmation, we will need more detail

(more classes), but as we progress toward

synthesis and presentation it becomes

more important to show general trends

rather than detail, hence fewer classes.

Furthermore, limitations on human visual

comprehension must also be taken into

account—the limit is about six levels of

color or gray scale shading in the context

of a map.

Are there natural breakpoints in crime

data? For example, in a robbery map of a

city we could embed the State, regional,

and national robbery rates as breakpoints.

This might be informative but could get a

political “thumbs down” if the local jurisdiction compares unfavorably. (Conversely,

it could be a popular approach.) Choices

available to cartographers in common desktop mapping packages are represented by

the drop-down menus shown in figure 2.14.

The choices available, and the relative

ease of using them, invite experimentation. How will a particular database look

when mapped in a particular way? What

method conveys the crucial information

with the least distortion and best visual

impact? Good maps are likely to result

from a working environment that encourages experiment because it is ultimately

through trial and error that most learning

is done. This is said not to invite a “shotgun” approach but, rather, to encourage

the responsible testing of options under

the assumption that alternative methods

of representation are tested for a reason

other than the sake of doing something

different.
Each of the alternatives typically employed

in data mapping is introduced here and

illustrated in figures 2.15 and 2.16.

■ Equal ranges or intervals. The data

range (difference between maximum

and minimum) is calculated and divided into equal increments so that the

within-class ranges are the same, such

as 1–3, 4–6, 7–9, and so on.

■ Equal count (quantiles). Approximately the same number of observations is put in each class. The number

of classes determines the technical definition of the map (quartile if there are

four classes, quintile if there are five

classes, and so forth). The term quantile is the generic label for data with

observations divided into equal groups.

This software option gives the user the

opportunity to enter the number of

classes desired. (This is the default in

MapInfo®.)

■ Equal area. Breakpoints between

classes are based on equality of area

rather than equality of range or an

observation count. If areas in a choropleth map vary greatly in size, this

type of map will differ from an equal

count map based on the same data. If

areas are roughly equal in size (such

as city blocks), the result will be similar to an equal count presentation.

■ Natural breaks. In this approach,

gaps or depressions in the frequency

distribution are used to establish

boundaries between classes. This is the

default in ArcView®, which employs a

procedure know as Jenks’ Optimization

that ensures the internal homogeneity

within classes while maintaining the

heterogeneity among the classes.

(For more details, see Dent, 1990,

pp. 163–165, and Slocum, 1999, 

chapter 4.)

■ Standard deviation (SD). SD is a

statistical measure of the spread of

data around the mean, or average.

In the literature of stocks and mutual

funds, for example, SD is often used

51

Mapping Crime: Principle and Practice

Chapter 2

Figure 2.14

Choices for class interval determination as presented in two widely used desktop mapping

programs. Left, ArcView®; right, MapInfo®.

Sources: ESRI, Inc., Redlands, California, and MapInfo Corporation, Troy, New York.
Table 2.1. Criteria for Selecting a Method of Classification

Criterion Equal Quantiles Standard Natural 

Interval Deviation Breaks

Considers 

P P G VG distribution 

of data along 

a number line

Ease of 

understanding VG VG VG VG

concept

Ease of VG VG VG VG computation

Ease of 

understanding VG P G P

legend

Legend values 

match range P VG P VG

of data in a class

Acceptable for U A UU ordinal data

Assists in 

selecting number P P PG

of classes

P=Poor G=Good VG=Very good A=Acceptable U=Unacceptable

What Crime Maps Do and How They Do It

as a risk index, since it expresses the

amount of price fluctuation over time.

In the context of crime, SD can be a

useful way of expressing extreme values of crime occurrence or portraying

various social indicators. Generally,

classes are defined above and below

the average in units of 1 SD. The

drawback is that this method assumes

an underlying normal distribution, or

bell-shaped curve, something of a rarity in social data.

■ Custom. As the label suggests, this

option allows users to determine class

intervals according to their own criteria,

such as regional or national norms and

thresholds determined for policy reasons.

Table 2.1 summarizes the criteria for

selecting methods to define class intervals

for maps, providing a guide with respect

to data distribution, ease of understanding, ease of computation, and other standards. (For a comprehensive discussion of

issues relating to the determination of

class intervals for maps, see Slocum,

1999, chapter 4.)

52 Chapter 2

Source: Thematic Cartography and Visualization, T.A. Slocum, 1999, figure 4.7, p. 74.

Reprinted by permission of Prentice Hall, Inc., Upper Saddle River, New Jersey.
Maps and statistics:

Exploratory spatial

data analysis

Some statistical methods have been mentioned in the preceding discussion, and

consideration of statistical concepts is

unavoidable when considering how best

to visualize numerical data. As noted earlier, because we can lie with statistics, we

can also lie with statistical maps. Indeed,

maps have been used throughout history

as propaganda tools (Campbell, 1993,

pp. 229–235), so potentially we can have

honest error as well as pure cartographic

deceit. Perhaps the greatest danger in the

mapmaking process is that people tend to

believe the information in maps (what

MacEachren, 1995, p. 337) called the

connotation of veracity), and they also

believe that maps are unbiased (the connotation of integrity).

But mapmakers, like other elements of

society, are culturally conditioned, selectively including and excluding data

according to the values of the responsible

parties. Given that maps can harbor many

possible errors and biases, both intentional

and accidental, it is incumbent on the

crime analyst to be aware of possible

sources of error and to work to avoid

them. Nowhere is there more scope for

distortion and misinterpretation than in

the preparation of maps based on numerical data. This is due to the potential complexity of the information and the infinite

set of display permutations, whether in

raw form or as some derivative measure

such as a rate or percentage.

Mapmakers can gain a preliminary understanding of what the numbers mean

through the process of exploratory spatial

data analysis. It is quite helpful to understand what the distribution of a set of

numbers looks like when expressed

graphically. Is this a normal (bell-shaped)

distribution with most observations clustering around the mean, or average, and a

few very low and a few very high values?

Is it a skewed distribution with extreme

values to the right (high values) or the

left (low values)? 

In the unlikely event of a normal, symmetrical, bell-shaped distribution, maps

created by all of the classing methods look

similar. Almost always, however, realworld data are somewhat skewed, and different classing methods produce maps that

look different and convey different visual

impressions to readers. 

Consider in some detail what will happen

when different methods are applied to a

data set that has a strong positive skew

(figures 2.16 and 2.17). 

53

Mapping Crime: Principle and Practice

Chapter 2

A Note on Skewness

A normal distribution is the familiar bell-shaped curve that is seldom seen

in crime data. Most crime data are positively skewed, meaning there is a

long right "tail" representing a few high values. Hot spots (high crime

areas) are geographic expressions of skewness, which presents difficulties

in mapping numerical data. See the box, How Much Exploration? and

figures 2.15 and 2.16.
What Crime Maps Do and How They Do It

Let’s review each histogram (or frequency

curve) and map in figures 2.15 and 2.16,

method by method.

■ Equal count. On the histogram, the

right tail (highest values of the distribution) is prominent because there are

few extremely high values. Thus, the

program has to seek the lower rankordered data values (farther to the left

on the histogram) to come up with the

13 observations for the class. (Note

that the number of observations per

class is uneven, ranging from 13 to

17.) The resulting map tends to visually exaggerate the seriousness of the

problem because color saturates more

map areas.

■ Equal range. Because the distribution

is right-skewed, equal range will tend

to favor lower data values. The two

lowest classes have 23 and 26 members, respectively, while the higher

classes have 7 and 3. The map contrasts with the equal count version,

now visually minimizing the problem.

■ Natural break. This method appears

to have struggled to come up with natural breaks, which is a problem, along

with breaks in awkward places. The

result here is quite similar to the equal

range breakdown, with cuts between

classes shifted to the left (lower values) as compared with the equal

range. It comes as no surprise that the

equal range and natural break maps

are quite similar.

■ Standard deviation. Here, the breakdown of class intervals is set with reference to the average, or mean, so that

an interval of 1 SD is established to

the left of (below) the mean (blue line,

0.47), and above the mean at the

same distance. The effect of this on the

right-skewed distribution is a symmetrical breakdown, with about as many

observations in the lowest (10) and

highest (9) classes and in the two middle classes (22 and 18). The visual

impression conveyed by the associated

map is close to the severity of the

equal count method. This

is due to the similar number of observations in the

top category. 

The basic point to be made

from this discussion is that

cases that may fall in a

given class by one method may be in a

different class by another. The only certainty is that the highest and lowest

values will always be in the top and bottom map classes, respectively. What

method is preferable? MacEachren (1994,

p. 47) noted that, “for any skewed data,

quantiles are a disaster for a presentation

map!” In the above example, quantiles

result in such a large data range in the

highest class as to be almost meaningless.

Standard deviation classes may be helpful

in some situations where the distribution

is not extremely skewed.

Note that a frequency curve shows skewness in the rank-ordered data values, but

54 Chapter 2

Best Choice?

Generally, natural breaks or equal intervals

will be the best methods for creating 

area-type maps in crime analysis.
55

Mapping Crime: Principle and Practice

Chapter 2

Figure 2.15

East Baltimore City homicide rate in choropleth maps using different methods. 

Source: Keith Harries.

Figure 2.16

Histograms associated with maps in figure 2.15 with class interval breaks (vertical yellow

lines) and normal distributions superimposed. 

Source: Keith Harries.
What Crime Maps Do and How They Do It

only a map can show skewness in geographic space. Are the high values distributed geographically in a random way or

clustered? Either method yields useful

information. If the high crime rates are

clustered, it may indicate a hot spot. If the

high rates are random, the net impact on

the community may be about the same,

but we are now unable to point to a hot

spot.

We can see an empirical relationship

between map scale and skewness, which

is minimized in a small area (large scale)

and maximized in a large area (small

scale). Think of it this way: A very small

area in the community, say 1 square yard,

can have no spatial skewness because

only one event can happen there. But as

the spatial scope increases (smaller scale

maps covering larger areas), the potential

for skewness increases because there can

be bimodal, or split, distributions in space

(as well as time). A clump of events can

occur in one small area with the rest

empty—an extremely skewed pattern.

This is what the crime scene is like on a

regional, national, or global scale. Clusters

correspond to opportunities presented by

the underlying controlling condition, population distribution. At the smallest scale

(region or world), the crime map is for all

practical purposes the same as the population map, but at larger scales (city or

neighborhood) we refine the view and see

that the presence of people actually means

variations in rates conforming to varied

social and physical environmental conditions. Also, at larger scales we will see

different patterns depending on the

denominators used to calculate crime

rates. 

Another way to visualize a distribution is

the use of a box plot, which shows how

data are spread in relationship to the

mean, median, mode, and quartiles, with

outliers symbolized in a special way.

(Outliers are values more than 1.5 box

lengths from either the 25th or 75th percentiles.) If we examine the HOMRATE

data set using the box plot routine in the

Statistical Package for the Social Sciences

(SPSS), the result appears as shown in

figure 2.17.5 Note that the box plot is an

alternative way of visualizing the same

data shown in figures 2.15 and 2.16. In

the box plot in figure 2.17, the red box

represents 50 percent of the data values,

with the median shown by the bold line

across the box. The 75th and 25th percentiles are the top and bottom of the box,

respectively. The ends of the Ts represent

the smallest and largest observed values

that are not defined as outliers. Although

the box plot seems to be repetitive, it provides a different perspective on the data—

one that complements the more frequently

used histogram. (For a detailed explanation, see SPSS documentation, such as

SPSS for Windows Base System User’s

Guide Release 6.0, p. 186.)

Only the immediate objective and the

available tools limit the amount of exploration and preprocessing crime mappers

do. Perhaps the single most important

exploratory step is the creation of a histogram, box plot, or comparable graphic

with which to visualize the shape of the

data and answer the fundamental question: Is it severely skewed or in some

other way not normal (e.g., bimodal or

double peaked)? How will this affect

maps, and what type of map will permit a

presentation that minimizes distortion and

56 Chapter 2
57

Mapping Crime: Principle and Practice

Chapter 2

accurately portrays the data? Again, this

examination of the data is the ideal. Not

all analysts will have the tools or the time

to go through this step. Nevertheless,

these possibilities are outlined here to

raise awareness of what constitutes the

best practice.

Map design

The field of map design has generated

substantial literature in cartography focusing on how people comprehend maps and

the impact of various design elements

such as symbol size, color, and line thickness. Also of interest is the impact of the

arrangement of a map within the map

frame as well as the merits and demerits

of various types of maps. 

Debate continues, for example, over the

dominance of choropleth maps to represent numbers. Opponents point to the

most obvious choropleth defect: its use of

one data value to represent an entire area,

an absurdity that becomes acute when

most of a geographic subdivision contains

virtually no human activity because of the

terrain or the existence of bodies of water.6

Muehrcke (1996) quoted Ronald Abler,

Executive Director of the Association of

American Geographers, who, in 1987,

said something to the effect that choropleth maps were an abomination that GIS

would soon eliminate through the use of

dasymetric mapping.7 (The death of the

choropleth map has been slow!) However,

the increased use of density surfaces in

various desktop GIS programs is a move

away from such heavy reliance on either

dot or choropleth modes of representation

and is consistent with the concept of areal

averaging—without slavish adherence to

political or administrative boundaries.

Map design is at once a technical and

an artistic effort. Dent (1990) devotes

5 chapters and about 120 text pages to

designing thematic maps; we can give

only broad consideration to a few issues

relating to typical parts of a map and how

they should be organized. The reader is

Figure 2.17

A box plot of 

homicide rate data.

Compare with histograms (see figure

2.16).

Source: Keith Harries.
What Crime Maps Do and How They Do It

referred to the following textbooks for a

full explanation, particularly on such

details as lettering and labeling: Campbell,

1993; Dent, 1990, 1993; Robinson et al.,

1995; and MacEachren, 1994, 1995.

It may be helpful for newcomers to mapmaking to make a flow chart in which the

design of the map is adjusted to ensure

that the map fulfills its stated purpose.

This activity may become less important

58 Chapter 2

How Much Exploration?

A histogram of the numerical data, as well as statistics for skewness and

kurtosis will help determine what kind of map would be most effective

and least misleading. Common statistical packages such as SAS® and

SPSS® enable the rapid production of these diagnostics. Also, Microsoft

Excel and other spreadsheets yield the following statistics as well as a 

histogram option. (In Excel, see the Tools menu, then Data Analysis.)

Interpretation: Values of the skewness and kurtosis are centered at zero. 

If either is relatively large, a nonnormal distribution is likely. See Norcliffe 

(1977) for more detail on this, and consult figures 2.15 and 2.16 for

graphic interpretations.

*HOMRATE is the homicide rate per 100 persons in a selected part of Baltimore,

Maryland. These statistics were used to compile figures 2.15, 2.16, and 2.17.

Source: Keith Harries.

HOMRATE*

Mean 0.74

Standard Error 0.06

Median 0.67

Mode N/A

Standard Deviation 0.47

Sample Variance 0.22

Kurtosis 1.44

Skewness 1.10

Range 2.20

Minimum 0.12

Maximum 2.32

Sum 42.43

Count (number of block groups) 57.00

Largest (1 case) 2.32

Smallest (1 case) 0.12

Confidence Level (95.0%) 0.12
over time as intuition and experience take

over from reliance on a formally structured process. Dent (1990, p. 316) lists

the following elements of the thematic

map, which could serve as a checklist for

inclusion:

■ Title (or caption).

■ Legend. 

■ Scale. 

■ Credits.

■ Geographic content (showing information that may not necessarily be included in the subject matter of the map,

such as orientation or north arrow).

■ Graticule (spherical coordinate system:

latitude/longitude, State plane).

■ Borders and neatlines (the lines that

bound the body of a map, usually 

parallels and meridians).

■ Symbols.

■ Labels.

Most of these elements are necessary in a

typical crime map. The principal exception

is the graticule (spherical coordinate grid),

which normally serves no useful purpose.8

Also, credits are rarely used because data

are likely to be locally derived. However,

if data sources are not self-explanatory,

credits clarify exactly where the data came

from. This information could be listed

under the body of the map using the keywords “source” or “data source.” We could

add author to the list to assist in the

process of accountability, inconspicuously

noting the name or initials of the analystcartographer in a corner of the map.

A useful approach to learning more about

design is to look at examples of crime

(and other) maps that have been deemed

acceptable by their respective audiences.

Fortunately, there is no shortage of maps,

whether on crime or on other phenomena.

The easiest access is via the World Wide

Web, and the appendix of this guide lists

some useful Web site addresses. Chapter 3

uses examples to discuss various applications of crime mapping. Here we confine

ourselves to outlining principles.

Dent (1990, chapter 13) has noted several

elements of map composition: balance,

focus of attention, and internal organization. 

■ Balance refers to the need to arrange

parts of the map in a way that enhances

its visual symmetry. However, the

crime cartographer may have little

flexibility with respect to balance

owing to inherent content limitations.

For example, the jurisdiction may be

extremely asymmetrical, making it 

difficult, if not impossible, to map

without leaving considerable white

space on the paper. Cities with long

“shoestring” annexations, like Los

Angeles, or States with long panhandles, like Oklahoma, are good examples of difficult map shapes. This

problem sometimes can be solved by

chopping the city or other area of

interest into its component parts. An

inset, or miniature map of the whole,

is used to show how the pieces fit back

together. Another solution is to routinely map individual precincts or districts

59

Mapping Crime: Principle and Practice

Chapter 2
What Crime Maps Do and How They Do It

under the assumption that the managers of those areas are first and foremost interested in seeing patterns in

their areas of responsibility. The drawback to this is that crime patterns do

not pay much attention to administrative or political boundaries, so that

looking at individual subdivisions in

isolation from the rest of the area may

cause someone to miss hot spots or

other useful patterns by fragmenting

them.

■ Focus of attention is a concept based

on the assumption that people read

maps like they read the printed page,

by moving their attention from upper

left to lower right.9 Hence the optical

center of a map is somewhat above the

geometric center suggesting that, ideally, the most significant information

should be closer to the optical center.

Again, this is easier to manage in theory than in practice. Still, it is a useful

concept to bear in mind because crime

analysts will sometimes have enough

discretion in design that the focus

of attention can be exploited to 

advantage.

■ Internal organization refers to the

alignment of the parts of a map or

individual maps on a page or within

a frame. Map elements should be

arranged in a logical way rather than

placed haphazardly on the page. The

core contents of the map, for example,

should dominate the space, and other

elements should be secondary.

According to Dent, contrast also is important to visual perception. Line, texture,

value, detail, and color are powerful tools

because they allow map elements to be

differentiated from one another. More contrast makes objects stand out, less allows

them to fade into the background. Line

thickness, or weight, can assist in this

process, and using more than one line

weight on the map can add interest.

Texture can add variety and draw attention to an important part of the map.

Value refers to the use of lighter or darker

shades of color, and detail draws the eye

in. As noted elsewhere, however, detail is

a two-sided coin. It adds interest, but

when used to excess it can cause clutter

and make the map illegible. If a map is 

to be reduced for publication, fine detail

may be completely lost in the reduction

process. Experiment with enlarging and

reducing on a photocopier to learn more

about how this works in practice. 

Color is extremely important in the

process of area differentiation. It is also a

complex issue owing to the physiological,

psychological, and physical processes

involved. Dent (1990, chapter 16) notes

that color has three dimensions: hue,

value, and chroma. 

■ Hue is the term given to color labels—

red, yellow, and blue, the primary

colors—and the millions of permutations derived from them. 

■ Value refers to the degree of lightness

or darkness of a color. GIS programs

can help you select color values by

providing color “ramps” (or series of

related shades or values of a hue) in a

visually logical sequence ranging along

an intensity spectrum. Colors vary

60 Chapter 2
along a continuum from light to dark.

For example, reds may range from

light pink to deep red, and blues may

range from sky blue to navy blue.

■ Chroma is understood through the

concept of color saturation. A less saturated color appears to contain more

grays, and a saturated color has no

gray and appears as the “pure” color.

In photography, some films have a

reputation for conveying more saturation than appears in natural scenes

(bluer blues, greener greens), “larger

than life” color that is pleasing to some

viewers but excessive to others.

Choices of color in maps need to be made

quite carefully because color may have

strong emotional connotations for some

readers. For example, should red be used

for a map of violent crime, given the symbolic connection to blood? It is tempting to

overload crime maps with warm colors,

such as red and orange, but the analyst

should be mindful of the symbolic effect

and the impact this may have on the

intended audience. 

Just as color makes maps and other

graphics come alive, color also enhances

our ability to mislead people with maps

through the use of inappropriate hues and

values. For example, a crime category that

is a local political “hot potato” could be

visually minimized through the use of

cool colors in subtle shades lacking saturation. The use of color in maps and

graphics is complicated by the fact that a

significant portion (8 percent of males and

0.5 percent of females) of the population

is at least partially colorblind. 

Crime mappers can take advantage of various models of color sequencing. GIS software typically defaults to a part-spectral

plan with shades from yellow to brown.

In a full-spectral plan, colors range from

warm to cool, and in a double-ended plan,

data values representing an increase (or

above average) are in one color and a

decrease (or below average) in another.

Increases (or higher values) are typically

shown in warmer colors, decreases (or

lower values) in cooler (see Dent, 1990,

p. 387). GIS software normally permits

the customizing of colors to fit your purpose.

Design, abstraction,

and legibility

Map design and abstraction are inseparable. The map design defines the level of

abstraction to be imposed. “To represent

is to abstract,” wrote Muehrcke, and

“abstraction frees us from the tyranny of

our physical existence” (1996, p. 275).

He presumably meant that it gives us

license to, so to speak, “mess with reality.”

Many of the issues that concern cartographers, such as the degree of distortion on

world maps, are of little concern to crime

61

Mapping Crime: Principle and Practice

Chapter 2

Using Colors and Shades

■ Use darker colors or gray shades for more or higher values. 

■ Use lighter colors for less or lower values.
What Crime Maps Do and How They Do It

mappers. Where should we focus our

attention when it comes to thinking about

abstraction in our maps? What can we

afford to ignore? Are any map elements

indispensable on most crime maps? 

Abstraction, the reduction of detail on

maps, permits us to design our maps in

ways that make them attractive and effective. Abstraction is like the sculptor’s 

chisel—it determines what remains of the

raw material and what form the finished

product will take. As noted earlier, most

map elements are dispensable at one time

or another, depending on the context. 

First and foremost, the analyst must consider the audience and the medium of

presentation. Will the map go to one person and be seen at arm’s length? Will it

be a page in a report? (If so, will it be in

color? How would the map look if it was

converted to gray scale?) Will it become a

transparency for an overhead projector or

a 35-mm slide? Will it be incorporated

into a digital projector production in

Microsoft PowerPoint® or comparable 

software? 

If a map is to be projected, lettering size

and line weight become quite critical. You

may have a brilliant map with potentially

great visual impact, but if two-thirds of

the audience can’t read the lettering when

it is projected, your creativity is wasted.10

Also consider the “demographics” of

the audience to be addressed: are they

younger? older? more educated? less 

educated? predominantly female? 

If the audience is not similar to the general population, some adjustments in map

design may be needed. Research has

shown, for example, that there may be

subtle differences in the way men and

women read maps (Kumler and

Buttenfield, 1996).

This begs the corollary question of 

exaggeration in maps to gain legibility.

Sometimes detail must be retained, but 

this may result in objects running together

owing to the thickness of the lines representing them. Line thickness may need to

be adjusted and objects may need to be

moved slightly to maintain visual separation. Bear in mind that line work on maps

often greatly exaggerates the true dimensions of linear features. A typical State

highway map may be used as an example.

On this map, interstate highways are

1/16th of an inch wide. The representative

fraction (RF) of the map is 1:380,160, or

6 miles to the inch, which represents a

width of 660 yards. This is probably, on

average, double the width of most interstate highways. By comparison, area

features such as a city block, a city, or a

county, should be accurately rendered

because exaggeration is not needed to

make them visible.

Even point data generally exaggerate the

size of the location at which a crime incident occurred or the address of the victim

or offender. Point symbols are actually

markers for general locations and should

be interpreted as approximations owing to

(a) the size of the point symbol and (b)

normal problems with address interpolation

touched on in chapter 4 of this guide. It is

tempting to see point data as the epitome

of accuracy, but this accuracy is relative. 

62 Chapter 2
Crime mappers might consider using more

perspective symbol landmarks or mimetics11 to help readers orient themselves,

particularly in metropolitan areas (see figures 1.2, 3.25, and 5.9). These symbols

are pictorial and characterize the landmarks

they represent, such as the use of an airplane symbol to represent an airport or 

silhouettes of familiar structures, such as 

a school, church, ballfield, cathedral, city

hall, or highrise tower. Such pictorial

devices are more important for lay audiences than for police officers, who are

familiar with the area, although the

assumption that all cops are equally familiar with entire cities or metro areas is a

fallacy. We—even cops—are victims of

our daily routines and the neighborhoods

they take us through. None of us can

comprehend entire metropolises, at least

not at the level of street name familiarity.

Summary

Chapter 2 has explained:

■ What crime maps should do.

■ How crime maps do what they do.

■ How to choose the right kind of crime

map.

■ Types of thematic maps.

■ How to choose class intervals in

numerical data.

■ Why data should be explored.

■ What is involved in crime map design.

■ How crime map design, abstraction,

and legibility are related.

63

Mapping Crime: Principle and Practice

Chapter 2

Map Design Questions to Consider

■ Is this the best map for the stated objective?

■ Is the scale appropriate?

■ Does the design account for both data representation and aesthetics?

■ Could a flowchart ensure the inclusion of all necessary elements?

■ Are the sources of data, authors of the map, and date of 

preparation shown?

■ Are balance, focus of attention, and internal organization

considered?

■ What colors work best?

■ Is the map legible in all the contexts in which it will be used 

(print, slide, fax, PowerPoint®, and overhead transparency)?
What Crime Maps Do and How They Do It

Notes

1. Circle radii are a function of the square

root of data values. A slightly larger value

(“Flannery’s Constant”) is used in some

programs to take into account visual

underestimation of areas (Campbell, 

1993, p. 272). This map was custom

designed and executed by cartography

students under the supervision of Thomas

Rabenhorst, Department of Geography

and Environmental Systems, University

of Maryland, Baltimore County.

2. This is sometimes referred to as a

“stepped” surface map as compared with

a “smoothed” surface. The former is based

on choropleth area subdivisions; the latter

is not.

3. For an interesting early example of 

isolines applied to crime mapping, see

Brassel and Utano (1979).

4. A map of this type, which has probably

never been produced, would demand data

from a global positioning system.

5. SPSS is described at http://www.spss.

com. Another widely used package, the

Statistical Analysis System (SAS), is

described at http://www.sas.com. See also

the Web site for S+ at http://www.

mathsoft.com/splus/.

6. San Bernardino County, California,

about the size of Denmark, is an extreme

example. The urbanized part is small, and

most of the county is part of the sparsely

inhabited Mojave Desert. Yet a choropleth

map of population density will show the

entire county as having the same density

(the average value), giving the visual

impression that the desert is populated.

7. Dasymetric mapping ameliorates the

areal averaging of the choropleth map by

recognizing the internal variation inherent

in the subdivisions. The result resembles

an isoline map with political or administrative subdivisions superimposed. (For

additional information, see Campbell

1993, p. 218.) For an illustration of what

Tufte calls the “mesh” map alternative to

64 Chapter 2

What’s Next in Chapter 3?

How maps can be designed to address specific issues and audiences,

such as: 

■ Patrol officers. 

■ Investigators.

■ Managers.

How maps can be used: 

■ To support community oriented policing and problem oriented policing.

■ In courts and corrections. 

■ When communicating with policymakers.
the choropleth map, see Tufte, 1990,

pp. 40–41.

8. Some police departments rely on a 

proprietary map system for navigation;

embedding that coordinate system in their

current mapping applications could be

helpful. In Baltimore County, for example,

locational references are to the grid of

maps published by ADC of Alexandria, Inc.

9. This assumption is culturally conditioned by the way the person reads,

which is itself language dependent.

(Arabic is not read in the same way as

English, for example.)

10. Take into account the size of the room

and how far the back row of seats is from

the image. Similar considerations apply if

you have a poster-size map to be displayed to an audience.

11. Mimetic symbols mimic the appearance of the real object. (See MacEachren,

1994, pp. 56–57; 1995, pp. 258–259.)

65

Mapping Crime: Principle and Practice

Chapter 2
67

Mapping Crime: Principle and Practice

Chapter 3

Chapter 3:

Maps That Speak 

to the Issues

This chapter discusses how map designs can address

specific issues and audiences. The underlying assumption that “one map fits all” is inadequate because each

audience has its own perspective on crime and how 

it can be prevented or controlled. Community leaders

may have the latest notorious incident on their minds.

Policymakers may be concerned about how to trim 

$1 million–$2 million from their budgets while making

the community safer. Members of the court and corrections communities may be concerned with overloaded

systems, overcrowding, and the ramifications of releasing offenders early. Investigators may need tools to

help them organize place-related facts and processes.

Police managers often worry about accountability,

resource allocation, displacement problems, and the

implications of demographic change. On the front lines

where patrol and community officers operate, community information is a core resource rarely available in 

sufficient quantity or quality. 

Patrol officers

Officers who spend time on the street are entitled to

the most up-to-date and comprehensive data related to

their patrol areas. These data should be easily accessible and user friendly.
Maps That Speak to the Issues

The most useful kind of information

should focus on recent area history, with

an emphasis on change. Effective policing

emphasizes patterns, and mapping and

understanding change are key to understanding these patterns. The most basic

information shows what happened and

where. For example, what has happened

during the past two shifts? Are new hot

spots emerging? Have significant developments occurred in outstanding cases? Is it

necessary to communicate with specific

neighborhood watch or citizen patrol representatives? Examples from Jacksonville,

Florida, and San Diego, California, are

shown in figures 3.1 and 3.2.

68 Chapter 3

Figure 3.1

An intranet map

showing calls for

service classified

by crime types,

Jacksonville,

Florida.

Source:

Jacksonville,

Florida, Police

Department.

Reproduced by

permission.

Figure 3.2

A map showing

auto thefts, Pacific

Beach area of San

Diego, California.

Source: Crime

Analysis Unit of the

San Diego,

California, Police

Department and

SanGIS. Reproduced

by permission.
Quick mapping systems that support

patrol functions have been developed by

several police departments. These include

Chicago’s Information Collection for

Automated Mapping (ICAM) program,

which defaults to a map of reported

offenses (based on the user’s selection 

of a crime type) during the previous 10

days in the district. Figure 3.3 shows an

example.

What are the basic elements of useful

maps for patrol officers? Primarily, maps

must be detailed and geographically legible. Generalization is acceptable on large

city or county maps, but maps of individual beats or posts can include details such

as street names, landmarks, and locations

of significant events relevant to an officer’s tasks. The ICAM model also incorporates some tabular data to give the map

added depth. For example, a map of criminal damage to vehicles could display a

table with the date, beat, time, address,

make and model of the vehicle, and 

other details for each incident. A map of

assaults could have embedded within it a

table with similar detail plus data on the

characteristics of the victim and suspect,

weapon used, and number of assailants.

Maps should be clear and unambiguous.

Contrast should be strong because maps

may be read under low light conditions

and may need to be understood quickly.

Maps are reference documents, so map

users do not memorize map detail any

more than they would memorize the 

content of an encyclopedia. A well-used

map will be referred to frequently, and 

this requires that the map be exceptionally

legible. Crime analysts may consider

establishing basic criteria for line weights,

font and symbol styles and sizes, color,

and shading. This should ensure that the

maps convey their meanings clearly under

all conditions. Maps lacking contrast or

containing small lettering, symbols, or

69

Mapping Crime: Principle and Practice

Chapter 3

Figure 3.3

A map showing residential

burglary offenses in

Chicago’s Sector 2.

Source: Rich, 1996, p. 13.
Maps That Speak to the Issues

poorly defined lines will be relatively hard

to read (figure 3.4).

Investigators

The documented applications of mapping

as a support tool for investigation suggest

several generalizations applicable to the

use of maps.

Maps:

■ Bring together diverse pieces of information in a coherent way.

■ Provide vivid visualizations of caserelated data and descriptive patterns

that may suggest answers to investigative questions.

■ Provide opportunities for spatial analysis with selection and query tools. 

(See chapter 4.)

■ Serve as tools to persuade managers to

deploy resources in a specific manner.

A recurring theme is that maps often

reveal a whole picture that is greater than

the sum of its parts. This happens when

many small and seemingly isolated and

insignificant pieces of evidence take on

critical importance when viewed as part 

of a pattern. 

Without maps, data may be incomprehensible or available only in the form of a list.

A list of suspects or pieces of physical evidence means little if key information is

70 Chapter 3

Figure 3.4

Contrasting maps, less

legible (top) and more

legible (bottom). 

Source: Keith Harries.
seen best in graphic form. Even a list of

addresses may be hopelessly confusing in

a metropolitan area with thousands of

streets.

These points are illustrated in several case

studies outlined by La Vigne and Wartell

(1998). In a McLean County, Illinois, case

involving rural burglaries, for example, an

inexpensive proprietary mapping program

was used to plot incidents on a county

map. Almost all incidents occurred close

to major highways, suggesting the

involvement of traveling criminal groups

that specialized in burglaries. The burglaries also seemed to occur close to cemeteries, which were thought to be lookout

places. Based on this information, more

patrols were placed around cemeteries,

leading to the arrest of persons belonging

to a group called the Irish Travelers.

Although there were no convictions, there

was a sharp decline in burglaries in the

region, suggesting that the group had

been displaced (Wood, 1998).

In a Knoxville, Tennessee, rape case, 

ex-offenders living near a crime scene

were mapped. Within 2 miles of the crime

scene, there were 5 sex offenders, 15

parolees, and 2 juvenile habitual offenders. When additional offenses occurred,

victims were able to identify the offender

from the suspect group selected according

to geographic proximity. The interpretation noted that “without the spatial analysis of the offender databases layered on

top of the crime scene map, the offender

information would not have been readily

known” (Hubbs, 1998).

In Aurora, Colorado, the time and day 

of occurrence, location type, method of

break-in, and property characteristics of

several burglaries were used to determine

that the burglaries were geographically

clustered. The events had taken place in

the afternoon in single-family dwellings,

and similar entry points and crime scene

behaviors (including damaging property in

the home) were evident. This information 

was distributed to the police department’s

burglary unit and patrol bureau, which

immediately identified and eventually

apprehended a suspect whose home

address was at the center of the observed

cluster (Brown et al., 1998).

Other relevant case studies involved

preparing murder trial evidence in St.

Petersburg, Florida (see chapter 5);

employing an autodialing system in

Baltimore County, Maryland (see chapter

5); predicting serial crime in Los Angeles,

California; and mapping evidence left by 

a murderer in Lowell, Massachusetts (see

La Vigne and Wartell, 1998, for details of

these and other cases).

Police managers

Police managers are confronted with

many challenges. Not only must they be

aware of crime problems, but they also

must be able to address problems involving labor relations, public relations, and

political influences. The following are 

typical issues affecting police managers,

which can be addressed by using mapping

as a management tool. The five issues 

are analyzing calls for service (CFS), hot

spot mapping, crime displacement, the

implications of demographic change, 

and accountability as exemplified by 

the CompStat process in New York.

71

Mapping Crime: Principle and Practice

Chapter 3
Maps That Speak to the Issues

Management issue 1: 

Mapping calls for service

to assist resource allocation

CFS are generally accepted as a crude

index of the demand for police services.

As such, they can be mapped. This

process uses either point symbols (each

symbol represents one or more calls) or

choropleth form (calls are assigned to 

specific geographic or reporting areas).

Although patrol officers find CFS maps

help indicate “where the action is,” maps

with greater detail are more useful. 

CFS maps are most useful as a tool to help

managers allocate resources. In Baltimore

County, Maryland, for example, descriptive

data on the number of calls that various

patrol units respond to are mapped (figure

3.5). This same police department then

analyzes and “weights” the calls for service to designate or modify police “posts”

or patrol areas. “Weight” in this context

means that CFS involving more serious

crimes are assigned higher values than

CFS regarding less serious incidents. The

weighted values are then totaled to indicate each post’s workload. As needed,

post boundaries are drawn (or redrawn)

to equalize the workload (figure 3.6). This

is done using a MapInfo® redistricting routine, which was originally intended to

help redraw political districts following

each census. The objective of political

72 Chapter 3

Figure 3.5

A map showing

descriptive data on

patrol responses to

calls for service. 

Source: Philip Canter,

Baltimore County,

Maryland, Police

Department.

Reproduced by 

permission.
73

Mapping Crime: Principle and Practice

Chapter 3

Figure 3.6

A map showing police

posts based on workload assignments by

reporting area. 

Source: Canter, 1997,

figure 4, p. 173.

Figure 3.7

A map showing the day

with the highest average

reported crime density,

Bronx County, New York,

October 1, 1995, to

October 31, 1996.

Sources: Map by

J. LeBeau, Southern

Illinois University, with

data from the New York

City Police Department.

Reproduced by 

permission.

redistricting is to maintain an equal number of residents in each political area to

maintain the “one person, one vote” principle—a process analogous to equalizing

incidents or workload per officer in the

police context (Canter, 1997). (See chapter

5 for another application of this method.)

Another example with implications for

resource allocation is shown in figure 3.7,
Maps That Speak to the Issues

74 Chapter 3

which illustrates the day of the highest

average reported crime density. In this

case, point data were aggregated into

more than 950 census block groups, and

the number of crimes per day, per square

mile for each block group, was calculated. 

Management issue 2: An

approach to hot spot mapping

Hot spots are discussed in more detail in

chapter 4. Here, we describe an application designed to identify specific locations

for increased law enforcement activity and

to help law enforcement managers solve

problems. This method, developed by Eck,

Gersh, and Taylor (in press), is called repeat

address mapping (RAM). It defines a hot

spot as “a single place with many crimes.”

The term “many crimes” is defined using

minimum plotting density—meaning 

simply that a minimum number of events

must occur in a specific place for it to

qualify as a hot spot. 

The hot spot designation procedure is

illustrated in figure 3.8. The steps include:

■ Sort places according to the number of

crimes so that the place with the most

crimes is at the bottom of the list and

the place with the fewest is at the top.

■ Divide the list into 10 equal sections,

with the top group containing the

fewest crimes.

Figure 3.8

A map showing the RAM

method applied to data for

East Baltimore, Maryland.

Note the distinctive difference between the pattern

for “all event mapping”

and the pattern for “repeat

address mapping.”

Source: Eck, Gersh, 

and Taylor, in press.

Reproduced by permission.
■ Designate addresses within the bottom

group as hot spots.

Management issue 3: 

Mapping displacement

In general terms, displacement occurs

when criminal behavior is replaced by

some other behavior or moved from one

place to another. Spatial displacement

occurs when offenders move from one

area to another in response to a law

enforcement effort. A fundamental problem in the analysis of displacement is the

natural and inherent conflict between the

local and general benefits of crime prevention. For example, a crime hot spot is

identified and a prevention program is 

put in place. This has the effect of chasing

offenders out of the area, only to move

them across the city, county, or State line.

Thus the local problem has been solved

(at least temporarily), but the net general

gain is zero—and could be negative if the

offenders are displaced to an area that is

more vulnerable because of weaker law

enforcement. Taking this line of reasoning

to its logical conclusion, it could be said

that preventing crime in one place causes

crime in another!

Barnes (1995) noted that the literature has

identified six kinds of crime displacement: 

■ Temporal. Offenders perpetrate crimes

at times seen as less risky.

■ Target. Difficult targets are given up in

favor of those easier to hit.

■ Spatial. Offenders move from areas

that may be targets of crime prevention programs to less protected areas.

■ Tactical. Tactics are changed to get

around security measures.

■ Perpetrator. New offenders take the

place of those who move, quit, or are

apprehended.

■ Type of crime. Offenders take up

another type of crime if one type

becomes too difficult to commit.

In theory, if perfect data were available,

all six of these displacement types could

be mapped. In practice, this is highly

unlikely, and from the perspective of 

spatial analysis, spatial displacement is

the prime candidate for mapping.

But mapping even spatial displacement

alone is difficult due to measurement

problems. Although it may seem simple

enough to establish a law enforcement

effort target area and a surrounding displacement area, measuring displacement

there is, in reality, far more complex. The

ability to measure displacement is also

affected by the impact of the enforcement

program, as well as the size of both the

target area and the displacement zone and

their existing crime levels.

For example, if the displacement area

already has a high level of crime, the effects

of the enforcement program could be indistinguishable from the normal variations in

criminal incidents in the displacement zone.

As shown in figure 3.9, the existing crime

rate is a key factor in isolating crime displacement. Displacement would be difficult

to identify in the top map. However, in an

area with little existing crime, displacement

may be obvious—or at least appear to be

obvious (bottom map). 

75

Mapping Crime: Principle and Practice

Chapter 3
Maps That Speak to the Issues

To suggest that spatial displacement

analysis is too difficult to be viable is an

exaggeration; managers and analysts

should assess viability on a case-by-case

basis. However, spatial displacement

analysis is harder than one might think,

and even a well-designed displacement

study may need to hedge its conclusions

(see Weisburd and Green, 1995; Reppetto,

1974; Hakim and Rengert, 1981; and

Barr and Pease, 1990).

Management issue 4:

Demographic change and 

its implications for managers

A key fact affecting police department

mapping is that some 26.3 million immigrants, about three times as many as in

1970, now live in the United States

(Escobar, 1999). This 10 percent of the

population is critically important to law

enforcement, whose primary function

requires interaction with the public.

Although many communities may feel 

76 Chapter 3

Figure 3.9

Maps illustrating

displacement.

The dense pattern in the top

map makes it

difficult to detect

displacement.

There is no such

problem in the

bottom map. 

Source: Keith

Harries.
little effect (particularly those that are

more isolated and rural), major metropolitan areas with many immigrants have

experienced profound social change. 

It is in such places that community policing takes on special significance. Not only

are “traditional” minorities (primarily

African-Americans and Hispanics) voicing

their opinions, but relatively new groups,

such as Bosnians, Dominicans, Russians,

Koreans, and Vietnamese, are becoming

more visible and politically articulate.

Matters are further complicated by the fact

that a specific national group, such as the

Vietnamese, may not necessarily constitute an ethnic group. Vietnam, for example, has 53 ethnic groups, leading to

potential stresses along ethnic lines.

Each group’s perceptions of what is legal

or illegal may differ sharply from local

norms. Opportunities for misunderstandings with law enforcement are rife, and

community policing officers must understand the cultural values and practices of

the groups they encounter. Language 

barriers mean:

■ Citizen reports may be difficult or

impossible to understand for officers

who are unfamiliar with a language.

■ Confusion and frustration over misunderstood reports may result in underreporting of crime because persons

who assume they will not be understood may stop reporting crimes.

■ It is unlikely that first-generation

immigrants will become police officers.

What does this have to do with crime

mapping? Because police agencies need to

know what is going on demographically

in their communities to react appropriately, mapping demographics and related factors may translate into better community

relations. The Washington Post published

the article “When Fighting Crime Isn’t

Enough: Fairfax, Montgomery [Counties]

Seek Police Chiefs Adept at Community,

Employee Relations” (Shear and Shaver,

1999). Surprisingly, perhaps, what was

missing from the discussion about recruiting new chiefs was the crime issue. The

debate was peppered with phrases such as

“effective management,” “comfortable

with changing demographics,” and “diversity.” Traffic generated more interest than

burglary!

A basic need is mapping where the minority and immigrant groups are located. Are

they scattered throughout the community

or clustered in distinct areas? What are

their institutions and facilities (e.g.,

churches and temples, community centers,

and schools)? What are the issues of concern to communities and what are their

locational attributes? A map such as the

one in figure 3.10 shows how census data

can be used to locate ethnic groups and

determine the overall degree of ethnic

diversity. Based on 1990 census data, the

figure illustrates the relative evenness in

the proportion of five ethnic groups in

census tracts. The index varies between

1.0 (equal numbers of all groups, maximum

diversity) and 0.0 (only one group in the

tract, minimum diversity). The ethnic

diversity map could be viewed as a model

for achieving the same ethnic distribution

77

Mapping Crime: Principle and Practice

Chapter 3
Maps That Speak to the Issues

in the police departments serving various

communities. A department does not match

the community if it is less ethnically

diverse than the area it serves.

Another possibility is to maintain a geographic inventory of minority and immigrant concerns so that managers can see

what and where the issues are. Community

leaders could be identified, perhaps by

subareas of the larger ethnic community,

to ensure that a contact person exists for

each neighborhood. Mapping can also be

used to show where second-generation

minorities are reaching adulthood, enabling

targeted police recruiting. The 2000 census

will permit this type of analysis on the

World Wide Web.

A major problem for demographic mapping is the lack of current population data.

Until data from the 2000 census become

available, alternative data sources are necessary. Analysts may have to improvise.

Field mapping may need to be done and

communities delineated on the basis of

visual checks, perhaps with the aid of a

global positioning system (GPS). Other

possible data sources include those on

school enrollments, utility hookups, and

building permits and inspections. Although

not yet fully operational, another promising

resource is the American Community Survey

(visit Web site http://www.census.gov). 

Management issue 5:

Accountability and New York’s

ComStat process1

New York City’s Computerized Statistics

(ComStat) process was initiated in 1994

in the form of crime control strategy 

meetings. As a result of sharp declines in

the city’s crime, the system is now widely

imitated. According to the police department, ComStat’s objective is “to increase

the flow of information between the

agency’s executives and the commanders

78 Chapter 3

Figure 3.10

A map showing

ethnic diversity

in 1990, 

Los Angeles,

California.

Source: Allen

and Turner,

1997.

Reproduced by

permission.
of operational units, with particular

emphasis on the flow of crime and

quality-of-life enforcement information.”

Crime strategy meetings, held from 7 to10

a.m. twice a week, are part of an “interactive management strategy” intended to

improve accountability “while providing

local commanders with considerable discretion and the resources necessary to

properly manage their commands.”

Precinct commanders present at the 

meetings twice a month.

The process format requires that precinct

commanders appear before the ComStat

meeting prepared to discuss crime and

policing in their areas. A big-screen 

computer map shows the precinct under

review. For example, a string of robberies

with similar circumstances might lead to

questions about known habits of robbery

parolees living in the vicinity. As this conversation develops, a map showing relevant parolee addresses illustrates the

discussion.

The crime reduction principles embodied

in the ComStat process are:

■ Accurate and timely intelligence.

Information describing how and where

crimes are committed, as well as who

criminals are, must be available at all

levels of policing.

■ Effective tactics. Tactics are designed

to respond directly to facts discovered

during the intelligence gathering

process. Tactics must be “comprehensive, flexible, and adaptable to the

shifting crime trends we identify and

monitor.”

■ Rapid deployment of personnel and

resources. Some problems may involve

only patrol personnel, but “the most

effective plans require that personnel

from several units and enforcement

functions work together as a team.”

■ Relentless followup and assessment.

To ensure that appropriate outcomes

occur, rigorous followup is necessary.

Underpinning ComStat crime reduction

efforts are eight explicit police strategies:

■ Getting guns off the streets.

■ Curbing youth violence in schools and

on the streets.

■ Driving drug dealers out of the city.

■ Breaking the cycle of domestic 

violence.

■ Reclaiming public spaces.

■ Reducing automobile-related crime.

■ Rooting out corruption and building

organizational integrity in the New

York City Police Department.

■ Reclaiming the streets of New York.

How does crime mapping fit in? The police

department explains it like this:

Among the command and control center’s

high-tech capabilities are computerized pin

mapping and the capacity to display

crime, arrest, and quality-of-life data in

many formats, including comparative

79

Mapping Crime: Principle and Practice

Chapter 3
Maps That Speak to the Issues

charts, graphs, and tables. By using

MapInfo software and other computer

technology, the ComStat database can be

used to create a precinct map depicting

almost any combination of crime and/or

arrest locations, crime hot spots, and other

relevant information. These visual presentations are a highly effective complement

to the ComStat report, since they permit

precinct commanders and executive staff

members to instantly identify and explore

trends, patterns, and possible solutions for

crime and quality-of-life problems.

A problem often overlooked in other police

departments—crime patterns that overlap

precincts—is addressed through an expectation that precinct commanders cooperate

with other commanders to address issues

of mutual concern. Typical ComStat

process maps are shown in figures

3.11–3.15.

Maps in support of 

community oriented

policing and problem

oriented policing

Three broad categories of maps can be

used in support of community oriented

policing (COP) and problem oriented 

policing (POP)2:

■ Crime and offender information.

This includes information about the

times, locations, and types of offenses,

repeated offenses, methods of offenders, property taken, points of entry,

linking evidence, types of vehicles

80 Chapter 3

Figure 3.11

A CompStat map

showing locations of

selected burglaries in

Brooklyn, New York.

Source: D. Williamson,

Center for Applied

Studies of the

Environment, Hunter

College, New York,

and New York City

Police Department.

Reproduced by 

permission.
81

Mapping Crime: Principle and Practice

Chapter 3

Figure 3.12

A CompStat map

showing the density

of selected burglaries

in Brooklyn, New York.

Source: D. Williamson,

Center for Applied

Studies of the

Environment, Hunter

College, New York, 

and New York City

Police Department.

Reproduced by 

permission.

Figure 3.13

A CompStat map

showing potential 

target areas from 

burglary densities in

Brooklyn, New York.

Source: D. Williamson,

Center for Applied

Studies of the

Environment, Hunter

College, New York,

and New York City

Police Department.

Reproduced by 

permission.

Figure 3.14

A CompStat map

showing counts of

burglaries within

potential target areas

in Brooklyn, New York.

Source: D. Williamson,

Center for Applied

Studies of the

Environment, Hunter

College, New York,

and New York City

Police Department.

Reproduced by 

permission.
Maps That Speak to the Issues

used, and suspect information, such as

personal appearance and case status,

which is also an aspect of accountability (figure 3.16).

■ Community and government

resources. These include information

about neighborhood watch groups,

storefront stations (figure 3.17),

parolees, probationers, tax assessment

and zoning laws, owner occupancy,

utility data, patrol beats, building footprints (planimetrics), alarm customers,

alley lighting, playgrounds, walls as

barriers, afterschool programs, high

social stress areas such as low-income

housing, liquor stores, and crime 

hot spots.

■ Demographics. These include information about population change, 

ethnicity, race, socioeconomic status

(SES), the percentage of femaleheaded households with children, the

age of housing, and the school-age 

population.

Extremely broad-based geoarchives are

very useful in COP and POP applications.

Because it is impossible to predict what

will be needed at any given moment, a

reference-type archive is necessary. The

ideal, noted in chapter 4, is an “enterprise”

database that crosses departmental lines

but remains accessible to all agencies. 

In addition, there is need for versatility

and flexibility in map preparation. For

example, line maps of streets will probably need to be superimposed over aerial

photos, which demands that their coordinate systems match (for more information, see chapter 4).

Maps and community

policing: The city of

Redlands, California,

approach

Under the leadership of Police Chief James

R. Bueermann, the city of Redlands,

California, has transformed its current

means of addressing neighborhood quality

of life by consolidating housing, recre82 Chapter 3

Figure 3.15

A CompStat map

showing differences in

counts of burglaries

within potential target

areas in Brooklyn,

New York.

Source: D. Williamson,

Center for Applied

Studies of the

Environment, Hunter

College, New York, and

New York City Police

Department.

Reproduced by 

permission.
ation, and senior services into the police

department’s Risk and Protective-Focused

Prevention (RPFP) program—a problemprevention model developed at the

University of Washington. RPFP facilitates

understanding of the causes and prevention of adolescent substance abuse, delinquency, violence, dropping out of school,

and pregnancy. Further:

By integrating the theoretical concepts of Risk Focused Policing

with the cutting-edge technology

of Geographic Information Systems

(GIS), Redlands has been able to

map community, family, and school

and peer group risk and protective

factors at the neighborhood level.

This enables the police departments

and the many community-based

organizations that share access to

this data to effectively focus their

limited resources on the most

problematic areas where the greatest

83

Mapping Crime: Principle and Practice

Chapter 3

Figure 3.16

A case status map,

Wilson, North

Carolina.

Source: Jeff Stith

and Wilson, North

Carolina, Police

Department.

Reproduced by

permission.

Figure 3.17

A photograph of a

storefront police 

station, Long Reach

Village Center,

Columbia, Maryland.

Geographic analysis

can assist in the

process of selecting

an appropriate location for neighborhood

facilities.

Source: Keith Harries.
Maps That Speak to the Issues

potential for change exists. 

[City of Redlands, 1999; see 

also Hawkins, 1995.]

The key is to mobilize collaborating 

institutions—schools, government, and

community-based organizations—to

reduce risk factors and foster “resilient

youth.” The seven maps shown in figures

3.18–3.24 provide a sample of the kinds

of maps prepared in support of risk

focused policing in Redlands.

Courts and corrections

As in other realms, law enforcement mapping can apply to any situation involving

the display or analysis of spatial data.

Courts and corrections are unusual in that

many of their applications may involve

large-scale representations of the type

referred to as high-resolution geographic

information systems and described in

chapter 6. This type of display is also

called forensic cartography in courtroom

situations. Such large-scale maps are useful for illustrating the location of objects 

in relation to other objects in a building, 

a room, or a prison setting where incidents

or gang activities have been problems.

Court and law enforcement mapping applications are in their infancy but will develop rapidly. A message on the crimemap

listserv in 1999, for example, referred 

to GIS applications in the Wisconsin

Department of Corrections. The message

noted that four neighborhood offices had

been selected for an enhanced supervision

project and they routinely exchanged

information with the Madison Police

Department about where offenders were

located. Other applications included using

mapping to reduce the overlap of agents

in a three-county region and for a graffiti

eradication project (Koster, 1999). In 

84 Chapter 3

Figure 3.18

A juvenile arrestees’

home addresses map

superimposed on a total

average risk map. 

Source: City of Redlands,

California, 1999.

Reproduced by 

permission.
85

Mapping Crime: Principle and Practice

Chapter 3

Figure 3.19

A map showing the

average risk of family

domain superimposed

on a map of community

assets providing skills,

opportunities, and

recognition.

Source: City of

Redlands, California,

1999. Reproduced by 

permission.

Figure 3.20

A domestic assaults

map superimposed

on a map showing

the family conflict

index.

Source: City of

Redlands, California,

1999. Reproduced by 

permission.

Figure 3.21

A nuisance crimes

map superimposed

on an index of 

community 

disorganization.

Source: City of

Redlands, California,

1999. Reproduced

by permission.
Maps That Speak to the Issues

86 Chapter 3

Figure 3.22

A map showing the

location of the top

10 calls for service

superimposed on

a map of police

beats.

Source: City of

Redlands,

California, 1999.

Reproduced by

permission.

Figure 3.24

A map of where bats

tested positive for

rabies.

Source: City of

Redlands, California,

1999. Reproduced by 

permission.

Figure 3.23

A comparison of

neighborhood 

survey traffic

responses with collisions and citations.

Source: City of

Redlands, California,

1999. Reproduced by 

permission.
addition to forensic and intrainstitutional

investigative work, GIS has applications in

resource allocation, offender tracking and

monitoring, and facility location. Some of

these are discussed in chapter 5.

Policymakers: 

The medium and 

the message

A police department’s in-house maps may

take on a routine character, as the audience learns what to expect in map format

and style. For an external audience, however, presentation needs to be handled 

differently. For example, how should data

be massaged, if at all? Should data be presented as raw frequencies or in the form

of a pin map, or should the numbers of

incidents be converted into rates adjusted

for population? Would other rates or ratios

be more informative?

Ultimately, only the analysts and those

doing the presenting can answer these

questions. The analyst should put herself

or himself in the position of the intended

audience and ask specific questions. Are

audience members likely to understand

maps? Will they understand your maps?

How can a point be communicated simply

and directly? Is the map too complicated?

Will this map serve its purpose?

These are extremely important considerations when addressing policymakers and

community groups. Such groups are political by nature and will likely attempt to use

information presented to them to their own

advantage. When information is complex,

the room for political maneuvering increases, and the underlying “truth” is more

likely to become a casualty. This does not

mean that sophisticated mapmaking is

taboo. Rather, it suggests that external

audiences may need to be educated about

the types of maps they can expect to see

and the pros and cons of each.

The need for education about map types 

is only one possible complication. In addition to being confused by different modes

of data presentation, external audiences

may have little or no appreciation for 

spatial analysis. This dictates simplicity, at

least in the initial stages of using maps to

publicly present crime data. Care must be

taken to provide a consistent style and

format, which includes the consistent use

of scale. A minor problem may be perceived as worse than it is if it is presented

in large type or vivid colors (figure 3.25). 

As noted, another issue to be considered

is management of the presentation. How

will the map(s) be presented? Using hard

copy? As a presentation? (If a presentation, will it use computer software, an

87

Mapping Crime: Principle and Practice

Chapter 3

To Massage or Not to Massage Data?

The risks of audience misunderstanding and confusion increase as you

stray from raw data by, for example, calculating rates based on the 

population or other conditions. Saying more, better, has a tradeoff. 

Is it worth the price? You be the judge.
Maps That Speak to the Issues

overhead projector, slides, or what?) By

fax? In a report? (If a report, will it be

printed in color or monochrome?) As an

e-mail attachment? As noted in chapter 2,

each presentation mode requires different

design considerations, including color and

scale. The difference between what works

in a fax presentation and what works in

large-format, color hardcopy is extreme.

The latter can accommodate detail and

color; the former demands expression in

plain, bold, and simple terms.

Community 

organizations

Similar considerations apply to presentations aimed at community organizations.

Again, the design and mode of presentation considerations need to be taken into

account. For example, community maps

could be produced for the following 

audiences and events:

■ Neighborhood watch groups.

88 Chapter 3

Figure 3.25

Two presentations of

the same data that

may lead to different

perceptions, i.e., a

“lesser” problem (top)

or a “greater” problem

(bottom).

Source: Keith Harries.
■ Neighborhood patrol groups.

■ Public meetings to address specific

problems (reactive).

■ Public presentations to promote goodwill between the police department and

the community (proactive).

In each case, the nature of the audience

influences map design, content, and use.

For example, neighborhood watch and

neighborhood patrol maps may be used in

the field. Therefore, their design must be

suited to less-than-ideal reading conditions. Public presentations should 

accommodate the audience’s level of

sophistication, which is often a reflection

of their age and education. If complex

street patterns or topography make the

mapped area confusing, the analyst may

use more icons on maps to “pictorialize”

the maps. However, great care is needed

to avoid patronizing audiences or giving

the impression that the police department

is putting something over on them by

using complicated maps. Figure 3.26

shows a map of community resources that

can be used as a basis for the formation of

constructive alliances.

Conclusion

If geographic information is useful in a

law enforcement context, ways can often

be found to present that information in 

a map. Geographic crime data alone are

not enough to create a meaningful map,

as they must be paired with a base map

and other data to make the map interesting. Every day, however, the demand for

“geographically enabled” data grows as

businesses, governments, and organizations begin to appreciate the value of

maps and spatial analyses.

89

Mapping Crime: Principle and Practice

Chapter 3

Figure 3.26

Community organizations in Detroit

mapped as part of

an effort to reduce

Devil’s Night arson.

Source: Martin,

Barnes, and Britt,

1998. Reproduced

by permission.
Maps That Speak to the Issues

Summary

Chapter 3 has explained: 

■ How maps can be designed to address

specific issues and the needs of special

audiences, such as patrol officers,

investigators, and police managers.

■ How maps can be used in support of

COP and POP.

■ The importance of the medium and 

the message in communicating with

policymakers.

■ How maps can be used in courts and

corrections.

90 Chapter 3

What’s Next in Chapter 4?

■ The role of GIS in crime mapping.

■ How GIS is used in law enforcement agencies.

■ How GIS affects what we can do and how we do it. 

■ Vector and raster formats. 

■ Geocoding. 

■ Filtering data.

■ Measurement using maps.

■ Constructing derivative measures. 

■ Hot spots.

■ Buffering. 

■ How large databases can be used in mapping and analysis. 

■ Data warehousing and data mining.

■ Factors demanding caution in the mapping process.

Notes

1. This section draws extensively on an

Office of Management, Analysis and

Planning (nd) document cited in the 

references; also see Dussault, 1999.

2. I am indebted to Sgt. Jeff Dean (San

Diego, California, Police Department) and

Dr. Richard Lumb (Director, Strategic

Planning and Analysis, CharlotteMecklenburg, North Carolina, Police

Department) for the elements contained 

in this list. Any misinterpretations are 

the author’s.
91

Mapping Crime: Principle and Practice

Chapter 4

Chapter 4:

Mapping Crime 

and Geographic

Information Systems 

The GIS revolution

Although it is tempting to think of geographic information systems (GIS) as a thoroughly contemporary

technology, its conceptual roots reach far back. A GIS

is based on drawing different spatial distributions of

data on paper (or other suitable media) and overlaying them on one another to find interrelated points.

Foresman (1998) notes evidence that this model was

used at the Angkor Wat temple complex (in today’s

Cambodia) in the 11th century. Modern geographic

information systems can be linked to developments in

the 1960s, including land use analysis in the United

Kingdom by Coppock (1962), development of the

Canadian GIS by Tomlinson (1967), and publication

of McHarg’s Design with Nature (1969). 

Early GIS efforts were restricted by the limitations of

older computer systems lacking memory and speed,

such as the 512k memory of the IBM 360/65, a 

computer widely used in the 1960s and 1970s

(Tomlinson, 1998). This limited the size of data sets

and made it difficult to simultaneously manipulate

multiple observations or large numbers of variables.

These constraints limited the attractiveness of GIS

technology to law enforcement agencies. Weisburd

and McEwen (1997) noted that police departments

typically lacked the computer resources and the base
Mapping Crime and Geographic Information Systems

maps necessary to support a GIS operation. Labor, startup, and operational costs,

such as coding incident addresses for the

computer, were prohibitive, and the field

lacked user-friendly software.

The earliest applications of crime mapping

appeared in the mid-1960s, according to

Weisburd and McEwen, who cited the work

of Pauly, McEwen, and Finch (1967) and

Carnaghi and McEwen (1970). Most early

crime maps were produced using the

SYMAP program developed at Harvard

University. Input required punched cards,

and output was produced on a line printer

that limited detail to the size of the printer

typeface. Shading of choropleth maps was

accomplished by overstriking printer characters so that they darkened (figure 4.1).

All maps produced this way were black

and white. Line symbol mapping (of auto

thefts, for example) was done on a plotter

(figure 4.2). (See Weisburd and McEwen,

1997, for additional information.)

Later, the SYMVU variant of SYMAP used

line renditions on a plotter to produce

three-dimensional visualizations, like that

shown in figure 1.13. Pioneering work

done in St. Louis by the police department

involved the establishment of a Resource

Allocation Research Unit with the objective of improving the efficiency of patrol

operations. The unit recognized that fixed

boundaries would have to be established

for crime mapping purposes. This was

done using so-called Pauly Areas, named

for (then) Sgt. Glenn A. Pauly, who designated mapping areas similar in size to

census block groups. Thomas McEwen

then devised a system for geocoding by

relating street segments to Pauly Areas.

This was the first time in an operational

setting that computerized visualization of

crime data was recognized as a management tool.

GIS applications in policing took off in the

late 1980s and early 1990s as desktop

computing became cheaper and software

92 Chapter 4

What Is a GIS?

A GIS is a computerized mapping system that permits information layering to produce detailed descriptions of conditions and analyses of 

relationships among variables.

Strictly speaking, any system that permits the representation and analysis

of geographic information is a geographic information system. The

acronym GIS is understood to refer to computer-based software, generally

in the form of a few popular proprietary software packages. Although a

prominent component of a GIS, proprietary software does not define a

GIS.

Even the acronym “GIS” is the subject of debate, with some arguing that

the “s” stands for “system(s),” while others object that this is too narrow,

and the “s” should stand for “science.”
93

Mapping Crime: Principle and Practice

Chapter 4

Figure 4.1

A “Flat-tone” map of total

index crime, St. Louis—

Part I—January 1967.

Source: Pauly, McEwen,

and Finch, 1967, p. 744.

Reproduced by permission.

Figure 4.2

A map showing auto thefts

in the Ninth District, 

St. Louis, January 1967.

Source: Carnaghi and

McEwen, 1970, p. 401.

Reproduced by permission.
Mapping Crime and Geographic Information Systems

became more accessible and user friendly.

To date, large departments have been

more likely to adopt the innovation; however, almost any police agency that wants

a GIS can have one. Foresman (1998, figure 1.2, p.11) recognized five ages of GIS

development.

The Pioneer Age, which lasted from the

mid-1950s to the early 1970s, was characterized by primitive hardware and software. The Research and Development Age

lasted into the 1980s and overlapped the

Implementation and Vendor Age, which

in turn lasted into the 1990s, when the

Client Applications Age began. The Local

and Global Network Age followed. 

Crime mapping came of age in the

Implementation and Vendor period, when

computing costs began to fall and software became more immediately useful.

Over the past decade we have also seen

more examples of police departments

commissioning customized versions of

software to meet their individual needs.

A survey of police departments conducted

in 1997–98 (Mamalian and La Vigne et

al., 1999) showed that only 13 percent of

2,004 responding departments used computer mapping. Slightly more than onethird of large departments (those with

more than 100 officers) did so, but only 

3 percent of small units did. On average,

departments had used computer mapping

for 3.3 years. Crime analysts were the primary users of mapping, with relatively

few patrol officers involved. The types of

data most likely to be mapped were:

■ Arrests and incidents, including Uniform

Crime Reports Parts I and II crimes.

■ Calls for service.

■ Vehicle recoveries.

The most frequent applications were:

■ Automated pin mapping (point data).

■ Cluster or hot spot analysis.

■ Archiving data.

The GIS perspective

Software

Other information gleaned from the computer mapping survey showed that 88

percent of respondents used off-the-shelf

GIS software, such as MapInfo® (about 50

percent), ArcView® (about 40 percent),

ArcInfo® (about 20 percent), and others

(about 25 percent). Some departments

used more than one package. Approximately

38 percent of departments that used mapping had done some kind of customizing,

and 16 percent were using global positioning system (GPS) technology. 

It would be expected that GIS computer

mapping would follow the classic bell

curve of innovation adoption (figure 4.3).

In the lower left are the early adopters,

followed by the early majority, the late

majority, and the laggards. A wider bell

means a longer process, or greater reluctance to adopt. GIS adoption will likely be

a rapid process because the technology is

simultaneously becoming cheaper and

more powerful.

94 Chapter 4
Vector? Raster? Say what?

You will probably hear the terms vector

and raster in mapping conversations.

How much do you need to know about

them? Enough to understand the jargon

and enough to make informed choices

about formats.

Raster maps store data in the form of a

matrix, or grid. A raster map represents

information by assigning each pixel, or

picture element, a data value and shading

it accordingly. The size of a raster data

matrix can be determined by multiplying

the number of rows by the number of

columns in the display. For example, if the

display settings on the computer read 640

by 480 pixels, the matrix has a total of

307,200 pixels—each of which would

have a data value on a raster-based map. 

Vector-based maps are built from digitized

points that may be joined to form lines, or

vectors, and polygons, or closed shapes.

(Digitizing means recording the exact

coordinates of each point along x-y axes.)

You will sometimes see the term topology

used in connection with vector format,

and this refers to the study of geometric

forms. This type of analysis is integral to

GIS but is largely transparent to users.

Each format has advantages and drawbacks. For example, lines in raster displays may appear jagged if resolution is

not high enough. Rescanning an image 

at a finer resolution greatly increases file

size. For example, if the 640- by 480-

pixel screen is doubled to 1,280 by 960

pixels, the number of pixels increases four

times from 307,200 to 1,228,800 pixels.

However, raster processing is quicker. 

Vector files are good at showing lines but

are labor intensive due to the need to

clean and edit vector data (Faust, 1998).

Applications that use the vector format

include emergency personnel routing and

determining whether a suspect could have

traveled a particular route in a given

95

Mapping Crime: Principle and Practice

Chapter 4

Figure 4.3 

Hypothetical bell

curves for GIS

adoption in police

departments.

Source: Keith

Harries.
Mapping Crime and Geographic Information Systems

amount of time. Most databases in urban

areas use vector format; examples include

street centerlines, precinct boundaries, 

and census geography. Vector files are 

not very good for managing continuous 

distributions, such as temperature or land

elevation. 

Although crime is not continuously distributed (crimes occur at separate points in

geographic space), we can estimate values

between known points to construct a continuous surface representation. The triangulated irregular network (TIN) data

structure is one frequently used way of

doing this. In it, points are connected to

form triangles, the attributes of which

become the basis for surface construction. 

Summing up raster-vector differences,

Clarke (1997) cited Bosworth’s analogy

about the work of composers Mozart and

Beethoven. Raster is Mozart (dainty little

steps), and vector is Beethoven (big

jumps from place to place). Another way

of characterizing the difference is to say,

“vector systems produce pretty maps,

while raster systems are more amenable

to geostatistical analysis” (LeBeau, 1995).

However, an alternative view argues that

whether a vector or raster format is most

useful depends on the type of analysis

and what it will be used for. For example,

crime densities are often calculated using

the raster format, even when the point

data for crime locations are in vector format. The vector data simply will be converted to the raster format. 

It bears repeating that the analyst should

know what format is used, why it is used,

and the limitations and possibilities of

each. A frequently encountered problem

involves conversion to another format.

Conversion from vector to raster is the

simplest. Going from raster to vector,

however, means that each line must be

converted on a pixel-by-pixel basis and 

a vector equivalent produced. This is

much more time consuming than vector 

to raster. Users may also convert from one

software system to the other (Clarke, 1997).

Because photographic and satellite images

are raster products, there is no choice

between formats unless conversion is

undertaken. As imagery of both types is

used more frequently in crime mapping,

we will see mixing of vector and raster

technologies. For example, a large-scale

aerial photo (raster) might be used as an

underlay for point crime data (vector) and

patrol area line files (vector). In most

cases, the crime analyst will not be aware

that different data formats are being used

because the importation and manipulation

will be seamless (figure 4.4). Although

photos and satellite images are in raster

format, they can be used to digitize data

into vector format. Specific features on an

aerial photo, such as the footprints of

buildings or physical barriers between

neighborhoods, are linear features amenable

to vector representation. Aerial photos are

often the source of other important base

data, such as street centerlines, with data

being digitally traced from the photo into

a vector system.

96 Chapter 4
Spatially enabling the

data: What is geocoding?

If we break the word geocoding into its

components, it means coding the Earth—

providing geographic reference information that can be used for computer

mapping. The history of geocoding is tied

to efforts at the U.S. Census Bureau to

find ways of mapping data gathered

across the country, address by address. 

In the 1960 Census of Population and

Housing, questionnaires were mailed to

respondents and picked up from each

household by enumerators. In 1970, the

plan was to use the mail for both sending

and returning surveys—hence references

to that census as mail out/mail back. This

demanded geocoding capability and, subsequently, the development of an address

coding guide (ACG). According to Cooke

(1998), the Data Access and Use Labs

created to accomplish this were responsible for creating today’s demographic

analysis industry.

The first geocoding efforts permitted only

street addresses to be digitized (admatch),

but the capability to show blocks and census tracts was soon added. This demanded that block faces be recognized, and this

was done by digitizing the nodes representing intersections. This, in turn, meant

that intersections had to be numbered and

address ranges had to be reconciled to the

correct block faces. The shape of the lines

on the map had to be precisely determined

and annotated, creating the map’s topology. The name given to this new block

mapping process was dual independent

map encoding (DIME) and, when combined with the address matching process,

it was referred to as ACG/DIME. By 1980,

ACG/DIME had become geographic base

file (GBF)/DIME. This was followed by 

a call for a nationwide, seamless, digital

map, to be called TIGER, short for topologically integrated geographic encoding

and referencing. Census Bureau geographer Robert Marx and his team implemented TIGER for the 1990 Census

(Cooke, 1998; Marx, 1986). 

97

Mapping Crime: Principle and Practice

Chapter 4

Figure 4.4

A map showing a vector

format superimposed over 

a raster format. ArcView®,

Baltimore County, Maryland.

The heavy blue lines are

police reporting areas 

(vector), triangles are 

aggravated assaults (vector),

and the underlay is

orthophotography (raster).

Sources: Reporting area 

polygons and assault 

data: Baltimore County 

Police Department.

Orthophotography: Baltimore

County, Maryland, GIS Unit,

March 1995, pixel size: 1

inch, compilation scale 1

inch=200 feet. Reproduced

by permission.
Mapping Crime and Geographic Information Systems

TIGER files contain address ranges rather

than individual addresses. An address

range refers to the first and last possible

structure numbers along a block face,

even though the physical structures may

not exist (figure 4.5). For each chain of

addresses between the start node and end

node, there are two address ranges, one

for odd numbers on the left, the other for

even numbers on the right. For a complete

explanation, see U.S. Census Bureau

(1997).

Geocoding is vitally important for crime

mapping since it is the most commonly

used way of getting crime or crime-related

data into a GIS. Crime records almost

always have street addresses or other

locational attributes, and this information

enables the link between the database and

the map.

How does the computer map in a GIS know

where the data points should be put? It

reads the x-y coordinates representing

their locations. When crime locations are

geocoded, the address is represented by x-y

coordinates, usually either in latitude and

longitude decimal degrees or in State-plane

x-y coordinates identified by feet or meter

measurements from a specific origin. The

big headache in working with address data

is that those data are often ambiguous and

may be erroneously entered in field settings. Common field errors include:

■ Giving a street the wrong directional

identifier, such as using east instead of

west or north instead of south.

■ Giving a street the wrong suffix or

street type (e.g., “avenue” instead of

“boulevard”); providing no suffix

when there should be one.

■ Using an abbreviation the streets 

database may not recognize (e.g., St.,

Ave., Av., or Blvd.).

■ Misspelling the street name.

■ Providing an out-of-range, or impossible, address. For example, a street is

numbered 100 to 30000, but an extra

zero is added, accidentally producing

the out-of-range number 300000.

■ Omitting the address altogether.

98 Chapter 4

Figure 4.5

A map showing

TIGER/Line® address

range basics.

Source: U.S. Census

Bureau, 1997, 

figure 3–1, 

pp. 3–9.
As you initially attempt automatic geocoding, street addresses are compared against

the existing street file database, and coordinates are assigned to the “hits.” This

process is sometimes called batch matching. The process is a one-time affair, done

automatically. Then, it becomes necessary

to deal with the “misses,” those addresses

that did not geocode automatically. 

Handling misses is done manually. The

bad address is displayed with the closest

possible matches the database includes.

Analysts use these options to select the

most likely match. This involves some

guesswork and risks geocoding errors. For

example, if the address entered is 6256

Pershing Street, and the only reference to

Pershing in the database is to Pershing

Avenue, then assigning the geocode to

“avenue” is not likely to be an error. On

the other hand, if the database also contains Pershing Boulevard, Pershing Circle,

and other Pershing suffixes, assigning

“avenue” could be wrong. This shows

how important it is to have standards for

entering addresses into a file, whether the

system deals with records or computerassisted dispatching (CAD).

Not all records in large data sets are likely

to be successfully geocoded. The title of

a section in a chapter in the MapInfo

Professional User’s Guide (MapInfo

Corporation, 1995), “Troubleshooting:

Approaching the 100% Hit Rate,” hints

at this. Some records may not be salvageable for a variety of reasons, including

ambiguity in an address that cannot be

resolved. Two other issues deserve mention, as well. One is that street addresses

are estimated along block faces and may

not represent true block face locations.

(For more on this, consult technical documentation.) Second, address matching can

be done for locations other than street

addresses, such as street centerlines, land

parcels, or buildings, depending on the

availability of each element in a spatially

enabled format.

Surprisingly, there is no minimum standard for geocoding. Maps can be produced

and distributed based on a 25-percent hit

rate. Readers may have no idea that a

map represents only a small fraction of all

cases. Worse, the missing cases may not

be randomly distributed, thus possibly

concealing a critical part of the database.

For example, in the geocoding process, a

person or persons may be inept or may

decide to distort the data. If this error originates in the field, it will probably have a

geographic bias based on the location of

the person making errors. Analysts may

consider reporting the hit rate for geocoding to better inform map readers. 

Although most map users may not understand the hit rate, a technical footnote

reading, “X percent of cases were omitted

due to technical problems, but, the police

department considers the pattern shown to

be representative of the total cases under

consideration,” may clarify the information.

(Seek legal advice for actual wording.) 

Given that there is no minimum standard,

the issue becomes: What hit rate is acceptable? This is a subjective decision, but a

60-percent hit rate is unacceptable and

may lead to false assumptions. Hit rates

this low should raise questions about a

crime analysis unit’s level of readiness

because low hit rates indicate that the

base maps in use and/or incoming data

are seriously deficient.

99

Mapping Crime: Principle and Practice

Chapter 4
Mapping Crime and Geographic Information Systems

A distinction needs to be made between

the hit rate and another geocoding measure, the match score. The latter is a score

derived from matches on each component

of the address. If all components of an

address are correct—street name, direction,

street type—the address will receive a 

perfect score. Missing or incorrect parts

reduce the score. This differs from the 

hit rate, which is the percentage of all

addresses that are capable of being

geocoded in either batch or manual mode.

Therefore, the hit rate and match score

can be used to set acceptable geocoding

standards. However, setting the acceptable

threshold of either rate too high or too low

may result in too few records making the

cut or, in the worst case scenario, incidents

being given wrong addresses, thus placing

crimes on the map where they did not

happen.

Like some other aspects of computer mapping, geocoding can be quite involved and

demand considerable practice and expertise before you can regard yourself as an

expert. The technical procedures used to

fix geocoding problems are beyond this

document’s scope. Readers are referred to

the user’s guides, online help, and reference guides that accompany software or

that are available on a proprietary basis.

Asking more experienced GIS users for

advice, perhaps in other departments of

local government (management information systems, planning, engineering, and

so forth), is another possibility. For additional information, see Block (1995).

Data selecting, filtering,

and mapping according

to useful criteria

The great power of GIS lies in its analytical

capability, in addition to its capacity to

quickly create maps of large, complex data

sets. This analytical power takes more

forms than can be described here, but a

few examples offer the reader the general

idea. (For an excellent overview, see

McEwen and Taxman, 1995.) Since procedures vary according to the GIS software

used, we offer a broad sketch of some

possible analytical approaches. Specific

details can be found in user’s guides, reference manuals, tutorials, and listservs

such as crimemap@aspensys.com, where

many analysts pose questions and get

useful answers on a variety of crime mapping topics, including how-to GIS questions. 

Selecting and 

displaying specific 

information

Perhaps the most basic analytical task in

using geographic information systems is

the process of selecting and displaying 

scientific information. As shown in figure

4.6, when objects, in this case aggravated

assault cases, are selected or “highlighted”

on the map with the select tool, their corresponding database records are highlighted in color or with a symbol located next

to the record. If the analyst wants to bring

together the selected records at the top of

the table for easier recognition and manipulation, they can be “promoted” (in

ArcView, for example) using the appropriate button.

100 Chapter 4
Mapping time

A more sophisticated process for selecting

information uses various criteria and is

referred to as “filtering” or “querying.”

Sometimes, you will see Structured Query

Language (SQL), which is a specialized

programming tool for asking questions of

databases. If the conditions you set are

satisfied, then certain cases are included

or retained in a new data set, as a subset

of the main data. The new file can then 

be saved, mapped, or manipulated in any

way. For example, the condition “Time is

greater than or equal to 1500 hours and

time is less than or equal to 2300 hours”

(written in computerese as time>=1500

& time <=2300) would select all cases 

in the 8-hour shift between 3 and 11 p.m. 

101

Mapping Crime: Principle and Practice

Chapter 4

Figure 4.6

A map and table frames

from ArcView® showing

the relationship between

objects selected on the

map and their highlighted

records in the table.

Source: Keith Harries.
Mapping Crime and Geographic Information Systems

Many variations are possible on the

“mapping time” theme. In figure 4.7,

maps of domestic disputes in CharlotteMecklenburg, North Carolina, show

change over a decade. The units of analysis were the central points, or centroids

(see the section “Centroid display” later in

this chapter) of 537 response areas. Idrisi

software (see appendix) was used to generate the two surfaces based on the square

roots1 of the data values for each response

area, resulting in a clear picture of substantial growth over the time period. In

1984, domestic disputes occurred mainly

in the north and west, as shown in green.

By 1993, calls had increased in number

and geographic coverage, particularly on

the east side and in the southwest.

Time geography is viewed through a different lens as shown in figure 4.8. Using

methods similar to those used to produce

figure 4.7, seven daily maps were constructed, followed by an eighth map to

denote the day of the week with the highest frequency of calls for each of the 537

response areas. Maps such as those in 

figures 4.7 and 4.8 could be used to allocate resources and to coordinate domestic 

violence prevention efforts.

Mapping space

Because crimes usually affect some neighborhoods more than others, maps may

focus on certain beats, posts, patrol areas,

communities, census tracts, neighborhoods, or other units. What is the geography of crimes in terms of council districts?

Could this information be used by the

police department to anticipate political

firestorms? Attention may not be confined

to such official areas, but may involve

informal or ad hoc areas, such as a 500-

yard radius around a drug market, bus

stop, or automatic teller machine, for temporary investigative purposes. Provided

that the boundary files for the official

areas are in the computer, queries can be

addressed to them. For example, you

could compute the rate of vandalism incidents per 1,000 housing units, per unit of

102 Chapter 4

Figure 4.7

Maps showing

domestic dispute

calls for service,

1984 and 1993,

CharlotteMecklenburg,

North Carolina.

Source: Map

by J. LeBeau,

Southern Illinois

University, with

data from the

CharlotteMecklenburg,

North Carolina,

Police Department.

Reproduced by

permission.
the general population, or per unit of the

male youth population. A few alternative

base maps are shown in figure 4.9.

Mapping incident types and

modus operandi

Conditions, or filters, can be used to refine

searches at any level the analyst chooses.

For example, the most obvious filter

would isolate all crimes of a specific type.

However, filtering can isolate crimes by

time of day, by neighborhood, and by

modus operandi (MO). Conditions can be

set to specify all the desired criteria, possibly resulting in the isolation of a cluster of

incidents that could be linked to the same

perpetrator. In figure 4.10, for example,

rape has been selected. These incidents

are shown without identifying victims by

using a large symbol to make the location

of each somewhat vague. The analyst

must trade some precision to accommodate the overriding need to protect 

victims.

Mapping attributes of victims

and suspects

Mapping by characteristics of victims, 

suspects, or both can also be useful and is

easily accomplished. For example, where

have females been assaulted? Is there 

evidence that a cluster of burglaries has

occurred at homes occupied by elderly

persons? 

103

Mapping Crime: Principle and Practice

Chapter 4

Figure 4.8

A map showing the

day of the week with

the most domestic 

dispute calls for service,

Charlotte-Mecklenburg,

North Carolina, 1993.

Source: Map by

J. LeBeau, Southern

Illinois University,

with data from the

Charlotte-Mecklenburg,

North Carolina, Police

Department. Reproduced

by permission.
Figure 4.9

Some alternate

base maps for use

in crime mapping.

Source: Keith

Harries.

Mapping Crime and Geographic Information Systems

Mapping other recorded 

characteristics

Possibilities for filtering are unlimited. You

can set as many time, space, victim, suspect, MO, or other filters as you wish,

given data availability. For example,

where are the armed robberies occurring?

What is the pattern of robberies at gunpoint within a 1-mile radius of drug 

markets? Where are juvenile offenders

victimizing elderly persons at gunpoint

during hours of darkness? Are spousal

assaults randomly distributed, or are they

clustered? 

The only limitation is the availability of

geocoded or geocodable information in the

database. A potentially useful map might

reflect the relationship between persons

on probation or parole and the types of

104 Chapter 4

Figure 4.10

A map showing 

the distribution 

of rape in the city 

of Cambridge,

Massachusetts.

Large symbols 

were used to avoid

presenting the 

specific locations 

of the victims.

Source: Cambridge,

Massachusetts,

Police Department.

Reproduced 

by permission.
crimes they have committed. For example,

a rash of robberies occurs in a neighborhood: Where are the robbery probationers

and parolees in that area? Do the MOs

match up?

Using GIS to 

measure from maps:

Aggregating data

Why measure? In the most general sense,

measurement is the foundation of scientific analysis, and it lies behind any quantitative analytical statement. For example,

what is the crime rate? To answer this we

have to know the base of the rate. Do we

want it per 1,000 persons, per reporting

area, or per patrol district? To calculate

this rate we must know how many crime

incidents have occurred, and, if we are

calculating a population-based rate, how

many persons there are per unit area. This

value, the base of our rate, is also known

as the denominator, because it is the bottom of the fraction used to calculate the

rate. Therefore: 

density = number of incidents per area

population per area

Here, “number of incidents per area” is

the numerator (top of the fraction) and

“population per area” is the denominator.

If there are 428 incidents and the population expressed in thousands is 3.7, the

rate is 428/3.7, or 115.68 per 1,000 persons. We can check that the calculation is

correct by multiplying the rate by the population to reproduce the original incident

count: 

115.68 x 3.7 = 428. 

A GIS program would do these calculations for you, but analysts need to know

how to provide appropriate instructions

before anything useful can be produced.

An application of density analysis is

shown in figures 4.11, 4.12, and 4.13.

First, the density of burglar alarm calls

was mapped using 48,622 locations 

for alarm calls in 1990 in CharlotteMecklenburg, North Carolina. Using the

ArcView Spatial Analyst extension, a grid

was used to generate the surface shown

in figure 4.11. Peaks occurred near the

central business district, along major

transportation arteries, and in the industrial northwest area. A similar map (see 

figure 4.12) was prepared to show the

density of the 10,288 burglaries reported

in 1990, focusing on both the central

business district and a radial, highwayoriented distribution. In the final phase,

the burglary density surface was subtracted from the alarm density surface, and a

query tool was used to select parts of the

surface where burglary density exceeded

alarm call density (see figure 4.13). This

map directs the analyst to areas where

displacement may be occurring and 

suggests areas for possible interventions.

Such interventions could include additional alarm installations or other targethardening measures (see figures

3.11–3.15).

The various types of measurement now

available in GIS programs are too numerous to describe. However, a few types of

measurement will be outlined to provide a

sense of what can be done.

105

Mapping Crime: Principle and Practice

Chapter 4
Mapping Crime and Geographic Information Systems

106 Chapter 4

Figure 4.11

A map showing

the density of 

burglar alarm

calls, CharlotteMecklenberg,

North Carolina,

1990.

Source: Map by

J. LeBeau,

Southern Illinois

University, with

data from the

CharlotteMecklenburg,

North Carolina,

Police Department.

Reproduced by

permission.

Figure 4.12

A map showing

the density of 

burglaries,

CharlotteMecklenberg,

North Carolina,

1990.

Source: Map by

J. LeBeau,

Southern Illinois

University, with

data from

the CharlotteMecklenburg,

North Carolina,

Police Department.

Reproduced by

permission.
Count incidents in areas

Although the primary need for counting

will be to total crime incidents, counting

other objects or events could be useful,

too. It may be helpful, for example, to

know how many and what types of 

alcoholic beverage licenses (beer, liquor,

restaurant, liquor store, and so forth) are

in specific areas. The information could

serve as a gross index of alcohol availability, although it would not necessarily 

indicate where or how much alcohol is

consumed or by whom. Or perhaps the

local building inspection agency supplies a

list of addresses of code violations. These

could be mapped and sorted by any relevant

areas, such as neighborhood association

jurisdictions or police operations areas. 

GIS software makes such identification

easy. Users may find it helpful to write

down the operation they want to do to

clarify the steps—especially if they anticipate several steps of filtering, measuring,

or other manipulations. In fact, this exercise is helpful for any kind of analysis.

For example, you might want to count

incidents of spousal abuse within patrol

districts, which in some programs might

be expressed in SQL something like this:

count spousal abuse.object

within patrol district.object

This tells the program to evaluate each

spousal abuse incident (“object”) and

determine in which patrol district it

occurred. Additional instructions may ask

the program to group incidents by patrol

107

Mapping Crime: Principle and Practice

Chapter 4

Figure 4.13

A map showing areas

with burglary density

greater than alarm call

density, CharlotteMecklenberg, North

Carolina, 1990.

Source: Map by

J. LeBeau, Southern

Illinois University,

with data from the

Charlotte-Mecklenburg,

North Carolina,

Police Department.

Reproduced by 

permission.
Mapping Crime and Geographic Information Systems

district by listing in a new table or file

each patrol district identification number

and the number of spousal abuse

incidents that occurred there.

Measure areas and distances

Area measurements are especially useful

for determining how many crimes occur

per unit area. This is not to be confused

with crime measurements by population

size or density. Generally, though not necessarily, crime densities will reflect population densities because population density

is an expression of crime potential. More

people means more potential victims and

offenders.

Distance measurements are also simple.

They require the use of ruler or tape software tools and, as with area measurements, the units can easily be changed.

Measure inclusion and overlap

Areas of interest in policing do not 

always fit together neatly. Police districts,

precincts, patrol areas, and so forth, may

not match school districts, council districts, census tracts, neighborhoods, 

community conservation districts, and

officially designated hot spots. GIS tools

allow users to measure overlaps between

areas or small enclaves in large areas

because any incidents found in a specific

area can be electronically identified. All

the crimes (or drug markets, liquor licenses, parolee addresses, injury accidents,

and so forth) in a specific area can be

selected and separated as a new data set

for special analysis. How are drug arrests

divided among council districts or neighborhood association areas? One GIS package, for example, includes the following

functions: contains, contains entire, 

within, entirely within, intersects. These

capabilities are typical of this type of 

analytical function.

Centroid display

A centroid is an area’s center defined as

the halfway point on its east-west and

north-south boundaries. However, the

centroid will not always be inside the

area. For example, an area may be 

L-shaped, in which case the centroid

theoretically would fall outside the area. 

A centroid is generally used as the point

where labels will be located by default and

where statistical symbols will be placed. 

Centroids can approximate the geographic

midpoints of areas, which may in turn

(theoretically) approximate the most

accessible points in the areas. Normally,

centroids are hidden, but they can be 

displayed on request. If you have area

objects without centroids, the centroid

(x,y) function can be used to generate

them. Centroids are used infrequently in

crime analysis and are typically used as

surrogates for other conditions, such as

accessibility. 

For surface-fitting purposes, the data 

values that apply to tracts, block groups,

or blocks could be assigned to their centroids, thus reducing areas to points for

computational convenience. Given the

common use of grid-based, surface-fitting

algorithms, however, this type of centroid

application is unlikely.

108 Chapter 4
Derivative measures:

How to create new 

indicators

Derivative measures are new variables

created by manipulating information in

one or more databases. The rate calculations discussed in the section “Using GIS

to measure from maps” are a simple form

of derivative measures that divide a crime

count by a population measurement 

to produce a population-based rate.

Generally, if you can express a soughtafter relationship using ordinary mathematical logic, then it can be calculated in 

a GIS. There you will typically find an

array of operators (+, -, =, *, “like,” 

“contains,” “and,” “or,” “not,” and so

forth), aggregates (average, count, 

minimum, maximum, sum, and so forth),

and functions (area, centroid, distance,

perimeter, day, year, and so forth). These

provide substantial versatility in general

analysis or in creating derived measures.

Getting a bit more fancy

The complexity of potential derivative

measures is unlimited. For example, you

might want to create a quality-of-life

measure for community areas that goes

beyond mapping income or real estate

values. This index could include such

variables as crime rate, education levels,

dropout rate, drug addiction measures,

and incivility reports. Provided the underlying data can be geocoded, or joined to 

a geocoded table, they can be mapped.

Then most, if not all, mathematical

manipulations can be done in the GIS. 

Apples and oranges

How do you combine variables measured

in different units, such as dollars, years,

or population? The quickest approach is 

to combine data in the GIS using overlays

and then to use “logical operators” such

as “greater than” or “less than” to reselect

groups using your criteria. A more indepth

process, but one that leads to greater

familiarity with the data, involves converting the data values into ranks (ordinal

scale measurement) before making any

calculations. Although you will lose the

ratio level measurement this way, you

gain the overwhelming advantage 

of being able to work with any units of

measurement. Another advantage of 

this process is that conversion to ranks

smooths the effects of poorly measured

data by intentionally making them less

precise. The conversion eliminates some

of the “phony” precision of data that are

inherently subject to error.

A problem that can generally be overcome

is that GIS software is typically weak in

statistical (as compared with purely mathematical) tools and may not be able to

convert data to an ordinal scale.2 This

could be done by using a statistical software package such as S+, SAS, or SPSS.

Or if the number of measures and areas 

is not too large, the work could be done

manually. Then ranks are summed to generate the index, after taking care to organize ranks so the lower numbers always

represent either the best or the worst, but

not a mix of both. The resulting numbers

will indicate a cumulative rank, or relative

status, that can be mapped (figure 4.14).

Crime data can then be overlaid on the

index map to show a possible relationship

with, for example, social dysfunction. For

109

Mapping Crime: Principle and Practice

Chapter 4
Mapping Crime and Geographic Information Systems

additional explanation, see Harries and

Powell (1994).

GIS as a tool for 

data integration

and exploration

A GIS is an ideal tool for bringing together

various databases that share common

geography. This function will become

more useful as the importance of data

integration is increasingly recognized. Not

only is there a need for more data integration, but there is also a need for recognition that most data used in policing about

land use, street centerlines, liquor establishments, bus routes, schools, subway

stops, and so forth are likely to come from

sources outside the police department.

Finding these types of data and adapting

them for crime analysis often take considerable initiative and may also demand

attention to data quality. This raises the

issue of metadata. This term refers to

data about data. Metadata provide information about the databases that you use.

(See “Minimum for Federal Geographic

Data Committee-Compliant Metadata.”)

Metadata standards are developed under

the auspices of the Federal Geographic

Data Committee (FGDC), a unit that coordinates development of the National

Spatial Data Infrastructure (NSDI). (See

the appendix for additional resources.)

All data with common geography can 

be overlaid. These layers may be manipulated—moved up or down, added or

removed (permanently or temporarily), or

made to become visible or invisible only

when the map is shown at a specified

scale. As noted on page 92, “What Is a

GIS?,” a fundamental concept in GIS

is layering. The various forms of this

process can provide a GIS with much of

its power and flexibility. 

110 Chapter 4

Figure 4.14

A map based on

an Urban

Pathology Index.

Source: Harries

and Powell,

1994, figure 2,

p. 54. Adapted

by permission.
111

Mapping Crime: Principle and Practice

Chapter 4

Minimum for Federal Geographic Data Committee-Compliant Metadata

Identification_Information: 

Citation: 

Citation_Information: 

Originator: This is the originator 

Publication_Date: 000000 

Title: This is the title 

Description: 

Abstract: 

A concise abstract of the data 

Purpose: 

(Types of projects that use the data, models, general use, illustrations, specific type of analysis, and so forth. Be specific if the data are geared toward

a narrow set of applications.)

Time_Period_of_Content: 

Time_Period_Information: 

Single_Date/Time: 

Calendar_Date: 000000 

Currentness_Reference: Publication date of sources 

Status: 

Progress: Complete 

Maintenance_and_Update_Frequency: Unknown 

Spatial_Domain: 

Bounding_Coordinates: 

West_Bounding_Coordinate: -109.9959 

East_Bounding_Coordinate: -108.0022 

North_Bounding_Coordinate: 37.0671 

South_Bounding_Coordinate: 35.9330 

Keywords: 

Theme: 

Theme_Keyword_Thesaurus: none 

Theme_Keyword: None 

Access_Constraints: none 

Use_Constraints: 

Limitations of data for use at certain scales and date ranges and for use with

other data 

Metadata_Reference_Information: 

Metadata_Date: 19950628 

Metadata_Contact: 

Contact_Information: 

Contact_Organization_Primary: 

Contact_Organization: Bureau of Land Management 

Contact_Address: 

Address_Type: mailing address 

Address: PO Box 0047 DWO

City: Denver 

State_or_Province: CO 

Postal_Code: 80225-0047 

Contact_Voice_Telephone: 555-5555 

Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial

Metadata 

Metadata_Standard_Version: 19940608 

Source: http://www.blm.gov/gis/meta/minimum.html
Mapping Crime and Geographic Information Systems

Combining data in geographic space provides opportunities for data exploration

and analysis that are lacking when geographic data are missing. An analyst may

want to see how robbery locations relate

to the locations of convenience stores.

Although this information may be in different databases, it can be brought together in GIS and the locations subjected to

the necessary analysis. For example,

buffer zones could be constructed at a

specified distance around each convenience store, and the number of robberies

in each zone counted. Then the percentage of robberies proximal to stores could

be calculated to provide an indication of

the importance of this type of store as a

robbery target. The possibilities offered by

this type of spatial analysis are virtually

unlimited. They include hot spot analysis,

stolen auto recovery directions and 

distances, delineations of gang turfs, 

calculations of area-specific rates, the 

construction of crime or other “surfaces,”

network analyses, boundary determinations, and others mentioned elsewhere.

Hot spots

Definition in geographic space

The term hot spot has become part of the

crime analysis lexicon and has received a

lot of attention. What are hot spots? How

do we recognize them?

A hot spot is a condition indicating some

form of clustering in a spatial distribution.

However, not all clusters are hot spots

because the environments that help 

generate crime—the places where people

are—also tend to be clusters. So any 

definition of hot spots has to be qualified.

Sherman (1995) defined hot spots “as

small places in which the occurrence of

crime is so frequent that it is highly 

predictable, at least over a 1-year period.”

According to Sherman, crime is approximately six times more concentrated

among places than it is among individuals, hence the importance of asking

“wheredunit” as well as “whodunit.” 

(See the appendix for hot spot-related

resources.)

A great deal of confusion surrounds the

hot spot issue, including the distinction

between spaces and places. Block and

Block (1995) pointed out that a place

could be a point (such as a building or a

classroom) or an area (such as a census

tract or a metropolitan region). However,

the former generally are regarded as

places, and the latter, with their greater

area, are spaces.

Sherman’s definition notwithstanding,

there is currently no widely accepted 

definition of a hot spot. Indeed, a rigid,

absolute definition may not be possible.

Except for programs with procedures that

self-define hot spots, such as the Spatial

and Temporal Analysis of Crime (STAC)

program (Block, 1995), jurisdictionspecific procedures to define hot spots

may make the most sense because they

will fit local conditions. In Baltimore

County, Maryland, for example, hot spots

are identified according to three criteria:

frequency, geography, and time. At least

two crimes of the same type must be present. The area is small, and the timeframe

is a 1- to 2-week period. Hot spots are

monitored by analysts until they become

inactive (Canter, 1997).

112 Chapter 4
In many cases, analysts may not be able

to define hot spots but may know one

when they see it. This makes comparisons

difficult both within and between jurisdictions.3 Furthermore, meaningful timebased analyses are problematic, because

hot spot definition criteria may not be

used consistently over time. 

Wide interjurisdictional and intrajurisdictional variations in environments also

make the application of absolute definition

criteria tricky. For example, the size and

shape of city blocks vary widely. West of

the Appalachian Mountains, city layouts

are usually dictated by the rectangular

land survey system, and blocks tend to be

fairly regular and rectangular. In the east,

where metes-and-bounds surveys prevailed, blocks are more likely to be irregular in shape and size. Densities also vary

greatly. Can the same definition criteria 

be applied in low-density areas as in highdensity areas? Crime-prone populations

are found in both environments. Can hot

spots exist in very low-density suburbs?

Residents would probably think so.

Hot spots and scale

Are hot spots purely a function of scale?

Some argue that any set of points in 

geographic space can be made into a 

hot spot if the scale is modified enough. 

At extremely small scale,4 all the crime

incidents in an entire metropolitan area

appear to be a hot spot (figure 4.15, upper

left). As scale increases, points become

more dispersed (figure 4.15, upper right

and lower left) until, at the largest scale,

individual points can be isolated (figure

4.15, lower right). The level of resolution

in the absence of absolute criteria makes

it possible to manipulate the presence or

absence of hot spots. However, absolute

criteria are difficult to apply in urban environments (Brantingham and Brantingham,

1995).

Generally, the hot spot concept is applied

to street crime rather than white-collar

crime, organized crime, or terrorist crime.

That a few white-collar crimes might 

overwhelm street crime in their economic

impact tends to be ignored. This may be

113

Mapping Crime: Principle and Practice

Chapter 4

Figure 4.15

An illustration

of the scaledependency of

hot spots.

Source: Keith

Harries.
Figure 4.16

A map showing hot

spot changes over

time: Detroit, 1994

and 1997.

Source: Martin,

Barnes, and Britt,

1998, figure 3, 

p.10. Reproduced by

permission.

Mapping Crime and Geographic Information Systems

because white-collar crime does not cause

the same kind of community fear and

anxiety as street crime. Similarly, if a city

experienced several terrorist bombings or

school shootings within 1 year, it is considered a hot spot that defies the normal

hot spot definition. There is a qualitative

aspect to hot spots; they refer only to 

limited crime types.

Hot spots in time

Just as hot spots can be described geographically, they can also be defined using

time-related criteria. An important question is: How long is a hot spot “hot”? 

The answer requires defining an incident

accrual rate within the spot, based on units

of time. Related decisions are needed to

determine whether the hot spot’s “temperature” is measured according to all confirmed crimes, all calls for service, specific

crimes, or other conditions. In a GIS

framework, hot spots (and/or incidents

within hot spots) can be color coded or

otherwise symbolized according to their

age.

An approach to monitoring hot spots over

time is shown in figure 4.16. This map

shows Devil’s Night arson hot spots in

Detroit in 1994 and 1997, using the STAC

program developed by the Illinois Criminal

Justice Information Authority. Although

not a mapping program itself, STAC can 

be used with most popular GIS packages.

(For additional details on STAC, see the

appendix and figure 4.20.)

Definition and measurement

What is a hot spot? Perceptions and definitions vary widely. Some analysts may

see a hot spot as any cluster that looks

interesting. Others define hot spots using

rigid, detailed criteria. A study by Buerger,

Cohn, and Petrosino (1995) found that

the latter group initially used the following

relatively formal criteria: 

■ Not more than one standard linear

street block (one side of the street

only).

114 Chapter 4
■ Not more than half a block from an

intersection. 

■ No closer to another hot spot than one

block.

The Buerger group further identified three

principal definition-related issues:

■ Public space. Hot spots were initially

limited to one side of the street, raising

the question of how street curtilage

(public space in front of private properties) would be treated. Common sense

dictated that if a patrol car was across

the street, technically outside the hot

spot, it should be considered in the hot

spot, so the definition was modified to

include both sides of the street.

■ Intersections. Ambiguities surrounded

the definition of an intersection. The

term eventually came to include not

only the street, but also adjacent sidewalks and buildings. Even when a hot

spot did not technically include all four

corners of an intersection, it was found

that the best viewpoint for seeing

around a corner might be on the other

side of the street, outside the hot spot.

Thus, all four corners of intersections

came to be included in hot spots.

■ One-block exceptions. Irregular

blocks with large open spaces contained some hot spots, making exceptions to the one-block rule.

In practice, hot spots are defined in

numerous ways, some with rigid criteria,

like those above, and others with a more

flexible approach. None is right or wrong.

Both approaches have pros and cons, and

an informal cost-benefit analysis can

determine the ideal criteria in individual

locations. The sharply defined criteria may

omit many commonsense exceptions (but

allow greater comparability in space and

time); softer rules permit easy adaptation

to local variation (but make comparisons

difficult).

Hot spot mapping

A detailed presentation of hot spot mapping methods is beyond the scope of this

guide. However, an investigation sponsored by the Crime Mapping Research

Center at the National Institute of Justice

in 1998 can offer some tips. This assessment found that most hot spot analysis

methods fall into one of five categories:

visual interpretation, choropleth

mapping, grid cell analysis, cluster

analysis, and spatial autocorrelation

(Jefferis, 1999; see also Canter, 1995). 

■ Visual interpretation. The survey

showed that, of the police departments

that do computer mapping, 77 percent

conducted hot spot analyses. Of these,

86 percent identified hot spots visually,

and 25 percent used a program to perform this task (Mamalian and La Vigne

et al., 1999). The problems presented

by the visual approach include overlapping points, points stacked on top 

of one another, making it impossible to

see how many incidents are represented5 (that is, only one appears at any

given location). Most serious, perhaps,

is that readers’ interpretations of point

data vary, resulting in different interpretations of the same patterns.

■ Choropleth mapping. Areas are

shaded according to their data values,

by either rate or frequency. The

115

Mapping Crime: Principle and Practice

Chapter 4
Mapping Crime and Geographic Information Systems

caveats mentioned in chapter 2 still

apply—class interval selection methods

will affect the appearance and interpretation of the map (see figures 2.15 and

2.16), as will color choices, shading

levels, and size variation among the

polygons. The latter elements tend to

draw attention to the largest areas,

particularly when they have higher

data values.

■ Grid cell analysis. A grid is superimposed over a map. Points within cells,

or within a designated radius from the

centers of the cells, are assigned to the

cells. The size of cells is variable and

affects the outcome of the analysis.

Small cells present higher resolution, 

at the cost of more computer resources.

With larger cells, resolution suffers, 

but computation is easier. What is the

advantage of grid cell analysis over a

pin map? First, adding points to the

grid solves the problem of “stacked”

data points, which occurs when multiple incidents occur at the same location

or nearby locations. Second, the points

are transformed into a smooth surface,

generalizing the data. (For related

methods, see the appendix: ArcView

Spatial Analyst Extension, Idrisi,

Vertical Mapper, the U.S. Department

of Justice Criminal Division Hot Spot

Slider.) Several examples of grid cell

analysis have been illustrated in figures 4.11, 4.12, and 4.13. Another

map of this type is shown in figure

4.17, which depicts hot spots in the

United Kingdom city of Nottingham

and police perceptions of hot spots.

This map was produced using the custom program known as SPAM (Spatial

Pattern Analysis Machine), which links

to MapInfo for the finished map (see

appendix). Variations of surface mapping

include three-dimensional renditions,

as noted in chapter 1. One key to readers’ perception of three-dimensional

maps is the degree of vertical exaggeration in the map. In the examples

shown in figures 4.18 and 4.19 of

Salinas, California, quite different types

of data (firearm crimes and gangs) are

shown in three dimensions. 

116 Chapter 4

Figure 4.17

A map showing

domestic burglary

hot spots and police

perception in the

Meadows area of

Nottingham, United

Kingdom.

Source: Ratcliffe and

McCullagh, 1998,

figure 1, p. 48.

Reproduced by 

permission.
■ Cluster analysis. Cluster analysis

methods depend on the proximity of

incident points. Typically, an arbitrary

starting point (“seed”) is established.

This seed point could be the center of

the map. The program then finds the

data point statistically farthest from

there and makes that point the second

seed, thus dividing the data points into

two groups. Then distances from each

seed to other points are repeatedly calculated, and clusters based on new

seeds are developed so that the sums

of within-cluster distances are minimized. (For related methods, see the

appendix: STAC, SaTScan, SpaceStat,

and Geographic Analysis Machine

(GAM.) Figure 4.20 illustrates hot spots

derived from the STAC method, which

performs the functions of radial search

and identification of events concentrated

in a given area (Levine, 1996).

117

Mapping Crime: Principle and Practice

Chapter 4

Figure 4.18

A map showing

firearm incidents

in Salinas,

California.

Source: Salinas,

California, 

Police Department.

Reproduced by

permission.

Figure 4.19

A 5-year analysis

of incident data

with an overlay 

of identified gang

turfs in Salinas,

California.

Source: Salinas,

California, 

Police Department.

Reproduced by

permission.
Mapping Crime and Geographic Information Systems

■ Spatial autocorrelation. This concept

relies on the idea that events that happen in different locations may be related. In a crime hot spot, for example,

underlying social and environmental

processes generate crimes in a small

area. Multiple events, such as the presence of drug markets, may have similar causes. This means that statistical

measures of this condition, known as

autocorrelation, can serve as hot spot

indicators (Roncek and Montgomery,

1995).

All methods of hot spot mapping should

produce similar maps if there are underlying and recognizable point clusters.

Something is wrong if a method produces

clusters where visual inspection indicates

there are none. However, analysis should

recognize that some methods involve

user-defined search criteria, and variations

in those criteria, such as differences in cell

sizes or search radii, can affect outcomes.

Buffering: Meaning 

and applications

A buffer is a zone around an object, such

as a school or intersection, that has some

investigative or analytical significance. For

118 Chapter 4

Figure 4.20 

A map showing 

robbery hot spots,

using STAC, West

Bronx, New York.

Source: Block and

Block, 1997,

figure 7.

Reproduced by 

permission.
example, drug-free school zones may be

defined using a 1,000-yard radius. Such

buffers can be drawn around schools and

overlaid on large-scale aerial photographs

so that field officers can easily recognize

the zone’s boundaries, even without

demarcating signs. Hardcopy maps can be

given to patrol officers as an aid in recognizing the zones. Buffering tools in GIS

programs make this a relatively simple

task (figure 4.21).

Techniques for selecting objects can be

used to identify certain types of events.

For example, what are the characteristics

of calls for service within 1 mile of high

schools? Calls for service can be identified

and separated into a new data set if they

are within the 1-mile buffer.

Buffers are shown as circles if the location

buffered is a point or street address, but

buffers do not have to be circles. For large

119

Mapping Crime: Principle and Practice

Chapter 4

Figure 4.21

An example of buffering used in conjunction

with the mapping of

related data. Red areas

represent 1,000-foot

drug-free school zone

buffers around schools,

large polygons represent police beats, and

point data represent

drug offenses.

Sources: J. Stith and

the Wilson, North

Carolina, Police

Department.

Reproduced by 

permission.

Figure 4.22

A map showing

polygon buffers

around public 

housing in

Baltimore, Maryland.

Source: Hyatt and

Holzman, 1999.

Reproduced by 

permission.
Mapping Crime and Geographic Information Systems

polygons like school campuses, parks,

apartment complexes, or industrial plants,

buffers can mirror the shape of the 

polygon. In figure 4.22, public housing

properties were buffered to evaluate the

relationship between public housing and

the surrounding neighborhood. The

underlying question was whether crime 

in public housing was committed mostly

by residents or by persons from the 

surrounding community. Analysis of 

incidents in the buffer zones can help

determine the answer, using data on 

the residential addresses of victims and

offenders. The same areas could be represented either by a circle buffer (if it is 

represented as a point or address) or as a

polygon buffer (if the area is mapped to

match its actual footprint). 

In a community policing example, questions may arise about the quality of street

or neighborhood lighting. Analysts can

consult with city engineers to learn about

the illuminated radius of various streetlights and their coordinates in the community. Then, using the buffer tool in GIS,

circles of the appropriate radii can be

drawn around each light location to create

a basis for assessing community concerns

about lighting quality (figure 4.23).

Also in the context of community

policing, an extremely disruptive phenomenon is house fires. This is especially true

in older neighborhoods with substandard

row houses, where the likelihood of fire

spreading from one home to adjacent

houses is great. In one study, buffers 

were drawn around residences where firerelated injuries occurred in the previous 

2 years. This, along with census data

indicating risk, helped establish zones that

were appropriate for the distribution of

smoke alarms. (This may seem like a fire

department function, but economic and

social disruptions can contribute to conditions in which crime flourishes, making

both fire and police functions relevant, as

with arson cases. This helps demonstrate

120 Chapter 4

Figure 4.23

The Grier Heights

neighborhood in

Charlotte, 

North Carolina,

showing street light

buffers and housing

tenure in 1996.

Source: E. Groff 

and CharlotteMecklenberg Police

Department.

Reproduced by 

permission.
the breadth of data that crime analysts

need access to.)

In Tornado Alley, the high-frequency 

tornado region in the Plains States, a 

community safety concern is the audibility

of warning sirens. Because the decibel

output of sirens is known and varies with

weather conditions, a GIS can be used to

map the audible zone of each siren. Areas

where sirens cannot be heard can be targeted by public safety agencies for special

action during tornado warnings. This type

of map could also serve as a blueprint for

locating new sirens.

Data, data, everywhere:

What’s an analyst to do?

Mapping outside data

Although most data used in crime analysis are generated and used within one

department, the need to integrate information from other agencies is becoming more

important. Unfortunately, outside data are

often in an incompatible format. What do

you do when you get a delimited or fixed

field ASCII file, for example? Table 4.1,

“Census data in ASCII,” shows data

almost exactly as they are presented on

the U.S. Census Bureau Web site, with

only slight editing to adjust the spacing.

The Federal Information Processing

Standard (FIPS) codes attached to all 

census geographic areas6 make up the 

first two columns. Starting in the left-hand

column, the State of Missouri FIPS code 

is 29. In the next column, the city of St.

Louis FIPS code is 510. Next are the tract

numbers, literal tract numbers, tract populations (P00010001), tract median family

incomes in 1989 (P107A001), and tract

per capita incomes in 1989 (P114A001).

Most GIS software can handle data compiled in a variety of formats, although

some variations may generate headaches.

MapInfo will open the following formats:

dBase, Lotus®, Microsoft Excel®, delimited

ASCII, some raster files (.tif, .pcx, and 

so forth.), AutoCAD® (.dxf), and others,

using either the Open or Import command. ArcView expects tabular data to 

be in dBase (.dbf), Info, or delimited text

(.txt) format. One solution to the somewhat limited data conversion repertoires 

of some GIS programs is to launder files

through a more versatile spreadsheet program and then transfer them to the GIS in

a more compatible format.

To do this, the user imports the foreign

data spreadsheet into Lotus, Microsoft

Excel, or Microsoft Access®, and then

exports it in a GIS-compatible format. This

way, a fixed-field ASCII file can be converted into a delimited ASCII or dBase 

format. This is done by parsing the fixedfield file in the conversion program, and

then outputting it in a delimited format.

Parsing is a process of instructing the program how to read the fixed-field data by

identifying the variables in each field and

dragging field delimiters to appropriate

locations. For example, the analyst

instructs the program that the case number is in columns 1–10, the address is in

columns 11–30, and so forth. Delimited

means that each data field is separated

from the next by a character such as a

comma or a tab. With delimiters, it does

not matter if data values have different

widths, as in the sequence 3.5, 14.276.

When the program recognizes the 

121

Mapping Crime: Principle and Practice

Chapter 4
Mapping Crime and Geographic Information Systems

122 Chapter 4

Table 4.1. Census Data in ASCII Tab-Delimited Format as

Acquired Directly From U.S. Census Bureau Web Site 

(http://www.census.gov) 

See text for explanation

(Selected census tracts for St. Louis, MO)

FIPS. FIPS. FIPS. STUB.GEO P0010001 P107A001 P114A001

ST CO. TRACT90

29 510 1011 Tract 1011 000002867 000032281 14262

29 510 1012 Tract 1012 000003287 000041559 15743

29 510 1013 Tract 1013 000004446 000036234 15401

29 510 1014 Tract 1014 000003075 000028322 11859

29 510 1015 Tract 1015 000003763 000021519 9787

29 510 1018 Tract 1018 000003773 000025197 9027

29 510 101899 Tract 1018.99 000000028 000000000 13929

29 510 1021 Tract 1021 000002820 000032625 15883

29 510 1022 Tract 1022 000006608 000040897 17131

29 510 1023 Tract 1023 000001834 000031157 14262

29 510 1024 Tract 1024 000002550 000034545 13226

29 510 1025 Tract 1025 000002253 000034911 13158

29 510 1031 Tract 1031 000003429 000039677 19250

29 510 1034 Tract 1034 000002200 000037222 13316

29 510 1036 Tract 1036 000001617 000033105 13240

29 510 1037 Tract 1037 000002883 000035461 14024

29 510 1038 Tract 1038 000004213 000039194 15466

29 510 1039 Tract 1039 000001229 000028375 11771

29 510 1041 Tract 1041 000003153 000030313 12649

29 510 1042 Tract 1042 000004076 000030660 14218

delimiter as a cue, it moves to the next

value.

You may receive data that consist of 

x-y coordinates, without the points themselves. In such situations, the coordinates

are used to generate the points in the GIS,

using a Create Points command that allows

users to select a preferred symbol and an

appropriate projection. (For information
about map projections, see chapter 1.)

After the points are generated, they can

be imported as a new layer on the map.

Data generated in the field, perhaps from

patrol cars using global positioning system

technology, can be treated in the same

manner.

Any database with an address or geographic reference included can be mapped,

provided the corresponding digital base

map is available. For example, you may

want to map census tract data. The census data are available, but the map of

tracts is not. In this case, the map is readily available to download off the Web, but

non-census tract maps must be acquired 

elsewhere.

Data warehousing

and data mining

Police departments generate volumes of

information. A single call for service ultimately results in its own pile of paper, and

computer files tracking all calls for service

grow rapidly. Data warehousing and data

mining provide sophisticated ways of storing and accessing information. 

A data warehouse is a megadatabase that

stores data in a single place instead of

storing them in project files or throughout

the local government or government

agency. Government agencies have been

slow to do this because agency politics

tend to create an attitude oriented more

toward defending departmental turf than

toward sharing data. A data warehouse

could assist with crime analysis efforts,

which often demand data from diverse

sources, such as the health, housing, traffic, fire protection, liquor licensing, and

planning agencies.

Law enforcement is primarily a local government activity, which often leaves police

agencies at the mercy of data managers

overseeing city or county information

technology functions. Ideally, data warehouses consolidate all jurisdictional databases and permit use of data from any

agency according to quality control standards. Data mining, as the label suggests,

involves digging nuggets of information

out of vast amounts of data with specialized tools. These tools are typically called

exploratory data analysis (EDA), which, 

in the context of mapping, can become

exploratory spatial data analysis (ESDA)

tools. An IBM software engineer (Owen,

1998) identified these as the factors that

brought data mining to the attention of

the business community:

■ The value of large databases in 

providing new insights is recognized.

■ Records can be consolidated with a

specific audience or objective in mind.

■ Cost reductions are achieved with

large-scale database operations.

■ Analysis is being demassified (futurist

Alvin Toffler’s term) meaning that the

information revolution permits the creation of specialized custom maps for

specific audiences.

Chapter 2 discussed hypothesis testing.

That discussion now comes full circle

because data warehousing and data mining make hypothesis testing even more

practical. Queries can be addressed to large

arrays of data, increasing the reliability of

responses. However, this is truer for historical questions than for current data.

123

Mapping Crime: Principle and Practice

Chapter 4
Mapping Crime and Geographic Information Systems

Cautions

Although GIS makes mapmaking relatively easy, it is not necessarily easy to make

good maps. The fundamental problem is

that fancy fonts, tables, maps, or diagrams can dress up almost any data.

However, just because data look good

does not mean they are. 

As a rule of thumb, do not blindly accept

the default settings in GIS programs.

Defaults apply to such steps as the selection of class intervals in choropleth maps

(see “Classifying map information” in

chapter 2), as well as the colors, symbol

types, and sizes. 

Boilerplate maps, produced regularly to

show specific needs such as weekly

precinct or division crime patterns, can be

fine tuned so they consistently convey 

the intended message. Problems are more

likely to arise with specialized maps. A

checklist may be a useful reminder of the

most important map elements and criteria:

■ Need. Is a map needed for this message or analysis? Could the job be

done as well or better with another

approach, such as a table, a narrative,

a chart, or conversation?

■ Data source. Are the data reliable? If

there are questions about data quality,

how can the audience be alerted? (By

using a map subtitle or map footnote?)

Are data so poor that mapping and

analysis should not be done? Who

decides if this is the case? 

■ Scale. Is the appropriate area shown?

Can the map be enlarged without 

compromising the message? 

■ Scope. Is the map trying to show too

much? Too little? Can more context be

added to better inform the reader?

■ Symbols. Would icons convey the

message more convincingly than

abstract default symbols? Note that

some icons are awkward shapes and

may have a minimum size, below

which they become meaningless.

■ Color. Misused color detracts from an

otherwise excellent map. Excessive use

of bright colors may hurt the eye and

repel the reader. Illogical color gradations may be confusing. Think in terms

of drawing the eye to important areas

(normally higher data values) by using

more intense color tones. Think about

how the map will be used. Color may

be irrelevant if the map is to be distributed by fax or printed in a document

that will not be reproduced in color. 

In such cases, color can be counterproductive. Even black-and-white 

(gray-scale) shades should be chosen

carefully if the document is to be

faxed. Gray-scales should not be too

subtle (variations will be lost), and

cross-hatched shading should be

coarse (lines relatively far apart) or

they will not hold up through the fax

process.

■ Lettering. Are the default font style

and size appropriate? Consider, for

124 Chapter 4

Rule of Thumb

Default settings in GIS programs

should not be accepted blindly.
example, whether the user may decide

to make the map into an overhead

transparency. Will the lettering be 

legible in that medium?

■ Methodology. What opportunities

does your software offer? (Hot spot

identification? Buffers? Filtering?)

Have those opportunities been taken

advantage of? Or have unnecessarily

glitzy methods only created confusion?

■ Privacy. Will this map reveal information about individuals who may be

subject to privacy restrictions? Most

data are in the public domain, including arrest records and court documents. Exceptions to this include the

practice of protecting the identities of

rape or sexual assault victims, and the

identities of juveniles.

Summary

Chapter 4 has explained:

■ The impact GIS has had on crime 

mapping.

■ How GIS is used in law enforcement

agencies.

■ How GIS affects what we can do and

how we do it.

■ The difference between vector and

raster formats.

■ What geocoding is.

■ How we can filter data and make useful maps according to specific criteria.

■ How GIS can be used to measure 

information on maps.

■ The meaning of derivative measures

and how they are created and used.

■ What hot spots are and how they are

defined, measured, and mapped.

■ What buffering is in the context of GIS.

■ How large databases can help with

mapping and analysis.

■ What data warehousing and data 

mining are.

■ Some factors that demand the exercise

of caution in the mapping process.

125

Mapping Crime: Principle and Practice

Chapter 4
Mapping Crime and Geographic Information Systems

Notes

1. Data transformations using square

roots or logarithms smooth data and

reduce problems associated with having

both very large and very small values in 

a distribution The effect may change the

distribution to a more normal, or bellshaped, curve.

2. The need for more integration of statistical

tools is gradually receiving more recognition, and the problem should diminish

over time. For example, a new package

known as Regional Crime Analysis GIS

(RCAGIS) developed for the BaltimoreWashington, D.C., region has an embedded statistical package, CRIMESTAT. 

Also, the S+ package by MathSoft®

(http://www.mathsoft.com/splus/) 

interfaces with ArcView.

3. Hot spots may be split by jurisdiction

boundaries in such a way that they fail 

to meet hot spot criteria on either side of

the line.

4. Reminder: Small-scale maps show large

areas, large-scale maps show small areas.

5. This problem of overlapping points can

be fixed with software manipulation.

6. Regions of all nations have FIPS codes.

Greater London, U.K., for example, is

UK17. For details, see: http://

webcentral.bts.gov:80/itt/T%26T/

resource/fipscode.pdf.

126 Chapter 4

What’s Next in Chapter 5?

■ Current events in crime mapping.

■ How to apply analytical crime mapping.

■ Criminal intelligence.

■ Crime prevention.

■ Courts and corrections.

■ Public information. 

■ Resource allocation and planning.

■ Census geography and analysis.

■ Crime mapping applications and improved effectiveness.
127

Mapping Crime: Principle and Practice

Chapter 5

Chapter 5:

Synthesis and

Applications

This chapter brings together concepts discussed 

previously and gives an overview of crime mapping

applications in selected areas of criminal justice.

Synthesis 2000

What are the most obvious characteristics of crime

mapping at the beginning of the new millennium?

Several come to mind:

Technology imbalance—most police departments,

except large ones (more than 100 sworn officers), 

do not use crime mapping technology.

Urban, suburban, and rural differences—in terms

of crime analysis and mapping, the perspectives and

needs of urban, suburban, and rural police departments greatly differ.

Incomplete geocoding—efforts to geocode rural

addresses are under way.

Geographic information system (GIS)

functions—GIS is used for descriptive, analytical,

and interactive purposes.

GIS mapping—GIS is used to represent information in

the form of points, areas (polygons), and lines.
Synthesis and Applications

Decreasing costs—more capabilities

become available as the cost of mapping

technology declines.

Crossjurisdiction alliances—these 

relationships recognize that criminal

behavior pays little heed to departmental

boundaries.

Theory and practice—the link remains

weak.

Data sharing—collaboration among 

State and local agencies is becoming 

more common.

Context—the “backdrop” is increasingly

being recognized as critical to understanding crime patterns and crime prevention.

Privacy issues—these issues become

more urgent as the ability of law enforcement agencies (and others) to link information to addresses and individuals

increases.

Public access—access to geographic

information increases with the use of 

the Web and systems such as ICAM

(Information Collection for Automated

Mapping) in Chicago.

Let’s consider each point in turn.

Technology imbalance. Why are most

police departments not using computerized

crime mapping? (Only 13 percent reported

using the technology in the 1997–98 

survey by Mamalian and La Vigne et al.,

1999.) Part of the answer lies in the very

different needs and capabilities of urban,

suburban, and rural law enforcement

agencies. The needs and resources of large

urban departments make computer crime

mapping practical. Crime rates, particularly

in so-called inner cities with larger police

departments, are generally higher than in

suburban or rural areas. A larger police

force also means that tasks can be more

specialized and that the probability of

having a staff dedicated to crime analysis

is greater. The political map is extremely

fragmented in some areas, such as Los

Angeles and Chicago, with numerous

small, incorporated communities outside

the central city. While the total population

in such metropolitan areas may be large

and the crime problems significant, political fragmentation decreases the likelihood

that police departments are, individually,

able to deploy specialized crime analysis

units.

Urban, suburban, and rural differences. Reasons for variations in the use

of automated mapping go beyond the size

of police departments and questions of

labor force specialization. Urban, suburban,

and rural environments differ fundamentally in a number of ways that relate to the

distribution of crime (Mazerolle, Bellucci,

and Gajewski, 1997). Among the obvious

differences are those relating to population

density, racial and ethnic diversity, social

cohesion, and economic health. Higher

population density means more potential

for crime in a given area. This does not

necessarily mean higher crime rates, however. A rural county may have a higher

population-based crime rate compared

with a city, but the city has more crimes

due to its having a larger population.

Urban law enforcement differs markedly

from that in rural areas, where communities

and residences may be widely separated.

128 Chapter 5
Rural policing may be just as fragmented

as urban policing. Each small town may

have its own police department with a

handful of officers, while the surrounding

area may be the responsibility of the sheriff or State police. (To add to the confusion,

in large cities sheriffs are not necessarily

involved in street-level criminal law

enforcement but may act as officers 

of the court, dealing with court orders, 

evictions, repossessions, and, perhaps, 

jail administration.)

Paradoxically, perhaps, response times to

calls for service (CFS) for the responsible

agency in a low-density rural area may 

be much longer than from its neighbor,

depending on the locations of police 

facilities. Concepts like patrol that are 

the bedrock of urban and suburban law

enforcement mean little in an environment like that illustrated in figure 5.1.

Response time, too, must be thought

about differently. It is easy to overlook

law enforcement environments that are

nonmetropolitan, since the problems that

attract most attention are in urban locations,

as are the media. Furthermore, the literature on GIS in policing is almost exclusively dedicated to urban case studies.

Because the application of GIS to lowdensity suburbs and rural environments 

is a new frontier and has been extremely

limited, hard questions need to be asked:

Does rural law enforcement really need

computer mapping? Can GIS improve rural

policing?

Incomplete geocoding. Historically,

geocoding efforts have had a distinctly

urban bias, for obvious reasons. The

majority of people lived in the cities, and

the census enshrined urban geocoding by

linking early address matching initiatives

to the areas that we know today as

Metropolitan Areas. Rural areas were

essentially impossible to geocode because

their rural route and post office (P.O.) box

addresses inhibited the construction of

links to the locations of housing units or

businesses. Preparations for Census 2000

include an aggressive effort to geocode

rural addresses. In some cases, 911 street

addresses are already available (typically

129

Mapping Crime: Principle and Practice

Chapter 5

Figure 5.1.

A photograph of a lowdensity environment in

the Oklahoma panhandle. In this rectangular

land survey grid area,

directions refer to miles

and compass directions. Privacy has a

different meaning than

in high-density urban

areas. On a map representing this lowdensity area, a dot

could easily be linked

to a specific household,

in sharp contrast to

high-density urban

environments.

Source: Keith Harries.
Synthesis and Applications

in the rural parts of metropolitan counties). In other cases, field workers go out

and record the locations of structures and

reconcile them to their rural route or P.O.

box number, if possible. This effort is

essentially a cooperative venture among

local governments, the U.S. Census

Bureau and the U.S. Postal Service.1

GIS functions. The uses of GIS in policing

can be characterized as descriptive, analytical, and interactive. Descriptive maps

can be equated with traditional cartography in that they tend to be a static picture

of information, albeit a very useful one, as

exemplified by the styles shown in figures

5.2, 5.3, and 5.4. Descriptive is not a

pejorative term—it is the foundation of

scientific investigation. Accurate description is an extremely valuable commodity

easily capable of providing answers to

questions. Accurate and timely description

is the foundation on which GIS rests.

Analytical maps go a step further and

consider relationships among map

elements or use methods based on spatial

statistics software, such as STAC (Spatial

and Temporal Analysis of Crime) or the

ArcView® Spatial Analyst. In interactive

mapping, the analyst enters and changes

map parameters “on the fly,” perhaps testing theories about fluctuating drug-market

boundaries, studying the displacement

effects of a crackdown, or examining how

buffering features may affect outcomes.

(For examples of analytical maps, see figures 5.7 and 5.9. For an example of what

was originally an interactive animated

map, see figure 6.8.)

GIS mapping. The predominant applications of GIS have involved the representation of point, area (polygon), and line

data for reasons that have been outlined

previously. However, as databases become

more integrated and newer technologies

130 Chapter 5

Figure 5.2

A map showing 

a burglary pattern

for a specific time

period in a specific

neighborhood in

Tempe, Arizona.

Source: Rachel

Boba and the

Tempe, Arizona,

Police Department.

Reproduced by

permission.
like global positioning systems (GPS)

become more commonplace, we might

expect the “traditional trio” of point, area,

and line to be supplemented by an everricher array of raster data in the form of

digital orthophotography and other photographic images. The wide availability of

orthophotography (often commissioned 

by local governments) combined with the

advent of inexpensive digital cameras and

(still somewhat expensive) digital video

recorders presages the fuller integration of

all georeferenced “visual” data. Most likely, traditional point, area, and line maps

will begin to be embedded with useful

raster elements, so that the user will have

131

Mapping Crime: Principle and Practice

Chapter 5

Figure 5.3

A map showing 

a scan of the 

robbery problem 

in specific neighborhoods in San

Diego, California.

Source: Julie Wartell

and the San Diego,

California, Police

Department.

Reproduced by 

permission.

Figure 5.4

A map representing

the regular crime

review process in

Cambridge,

Massachusetts, with

housebreaks classified according to

various time criteria.

Source: Cambridge,

Massachusetts,

Police Department.

Reproduced by 

permission.
Synthesis and Applications

the choice of seeing a map or bringing up

an orthophoto and/or a ground-level

photo of the location of interest. (See

chapter 6 for more on orthophotography

applications.)

Other nontraditional applications include,

for example, public safety events, in

which police, fire, and other agencies are

brought together in a common effort to

alleviate a natural disaster. A map constructed for this purpose (figure 5.5)

details data that provided general

locations of police and fire units during a 

catastrophic flood in Dallas, Texas.

Ever-decreasing costs. Decreasing costs

have brought mapping technology within

the reach of agencies that would not 

otherwise have been able to acquire it. 

In the early days of the Information Age,

equipment and software often cost more

than the operator; now that situation is

reversed. But the impact of less expensive

technology goes deeper. Not only can

agencies put computers on their workers’

desks, but those computers are increasingly

powerful and thus provide additional

opportunities that slower or memorychallenged devices could not have accommodated. For example, very large raster

files, unmanageable until recently, no

longer pose as much of an access problem

as they once did.

Crossjurisdiction alliances. The belief

that “all politics are local” has inhibited

collaboration between police agencies. 

The mantra has been that local problems

should be solved locally, although the use

of State or Federal dollars was acceptable

provided not too many strings were

attached. Unfortunately, offenders have

not subscribed to the notion that they

should recognize city, county, and State

lines.

The following inconsistencies among law

enforcement agencies have acted to make

political boundaries “law enforcement

opaque” rather than transparent or 

invisible, as criminals perceive them:

■ Different radio frequencies.

132 Chapter 5

Figure 5.5

A map showing 

locational 

information 

relating to a flood

in Dallas, Texas.

Source: Mark

Stallo and the

Dallas, Texas, 

Police Department.

Reproduced by

permission.
■ Different protocols for hot pursuits.

■ Agencies competing with one another

in hot pursuits and investigations.

■ Lack of information sharing and coordination between administrative units

and/or agencies (referred to as “linkage

blindness” by Rossmo, 1995).

Mapping has helped break down such barriers due to its power to provide visual evidence that criminal groups or individuals

move across boundaries at will, sometimes

intelligently exploiting the lack of communication between agencies. The increased

interlinking of databases needs to be coupled with jurisdictional interlinking so that

the official view of crime more closely 

corresponds to regional reality. Politically

bounded areas, whether cities, counties, or

States, rarely conform to social areas. Until

policing areas more closely conform to or

recognize social areas, crime analysis and

prevention will be stymied to some degree.

Crime mapping has tended to focus on

technical issues, but the bigger picture—

Are we mapping and analyzing the most

appropriate areas?—also deserves attention. Crime can be a regional phenomenon. Regional problems call for regional 

solutions.

Theory and practice. Crime mapping is

typically based on experience and observation, with a weak or nonexistent 

theoretical foundation. Empirical and theoretical perspectives battle each other in

the here-and-now world of law enforcement. When tangible flesh-and-blood

problems need to be taken care of immediately, theory is at best abstract, at worst

completely irrelevant. But theory does

have a place as a conceptual backdrop—

a reference base that can provide consistency to our analyses and tactical responses. Eck (1997) pointed out that as the

theoretical content of maps increases, it

becomes easier to make sense of the data

(see also Eck and Weisburd, 1995). In

other words, if a map shows only crime

locations, indepth explanation of pattern

is next to impossible. But if other elements of context are included, such as the

socioeconomic environment or locations 

of drug markets or of abandoned housing,

(any elements that theory would lead us

to expect to be linked to the crime pattern

in some way), then understanding is 

likely to be enriched. For example, a CFS

map, such as in figure 5.6, may be substantially more meaningful when the CFS

are displayed along with housing code

violations. “Negative” information showing where the anticipated link between

conditions fails to apply may be just as

useful as “positive” information showing

where the link does apply.

Data sharing. Local and State governments are finding that data gathered by

one agency might be valuable to others.

This is not surprising, given the baffling

complexity of social problems, including

crime. Social scientists have long recognized that social systems are in some

ways like natural ecosystems: change

something and everything else changes 

to some degree. Land use patterns and

changes, demographics, transportation

system configurations, the weather, and

the strength of social controls embedded

in the culture—these and many more factors influence patterns of crime. It makes

sense to give crime analysts access to 

the rich variety of data they need to help

them answer the widely varied questions

that come their way.

133

Mapping Crime: Principle and Practice

Chapter 5
Synthesis and Applications

Gradually, and inconsistently in terms of

geography, “community” approaches to

problem solving dictating collaboration

and data sharing among agencies are

gaining popularity.

Context. A relatively recent trend in

crime analysis emerging from the community policing movement has been the

increasing tendency to see crime “in context” rather than as a self-contained phenomenon with self-contained solutions. 

A broad view is needed, one that incorporates understanding of social background

and crime patterns. Complete preoccupation with patterns and their immediate

causes is a kind of professional shortsightedness that may miss fundamental causal

processes (see Sherman et al., 1998, for

more on the broad view of crime prevention). Crime analysis that ignores this

wider perspective, or backdrop, runs the

risk of ignoring important connections to

community-based processes. This again

reinforces the importance of making a

variety of data available to police officers

and crime analysts alike.

Privacy issues. Privacy questions are

touched on elsewhere in this guide, but

they also deserve a mention in any discussion of synthesis. In marked contrast

to the cultures of many other developed

nations, U.S. culture is quite resistant to

government intrusion, even when that

intrusion seems to be well intentioned 

and in the apparent best interest of the

majority. Along with this goes a degree 

of mistrust of law enforcement, a posture

reinforced by high-profile events such as

the Rodney King affair in Los Angeles,

the Abner Louima incident in New York

City, and the Branch Davidian standoff in

Waco, Texas. Fears of privacy violations

by law enforcement are only part of

broader societal concerns about privacy

and the inherent mistrust of authority.

These concerns were exemplified by the

controversy surrounding the activities of

134 Chapter 5

Figure 5.6

A map showing 

substandard housing

and calls for service

in the Grier Heights

neighborhood,

CharlotteMecklenberg, North

Carolina.

Source: Elizabeth

Groff and CharlotteMecklenberg, 

North Carolina,

Police Department.

Reproduced by 

permission.
Image Data, LLC, a small New Hampshire

company that in 1999 attempted to build

a national database of driver’s license

photographs, ostensibly to combat check

and credit card fraud. After Colorado,

Florida, and South Carolina had contracted

to supply their license pictures, it was discovered that the photo file was also to be

used to combat immigration abuses, terrorism, and other identity-related crimes.

It then became known that Congress had

contributed $1.5 million to the effort and

that the U.S. Secret Service had lent a

hand, elevating the controversy to new

heights and provoking initiatives from 

the three States to cancel their contracts

(O’Harrow and Leyden, 1999; for a more

detailed analysis, see Paisner, 1999).

This type of data gathering is one of

many ways in which data relating to individual persons, families, or households

can be accessed and compiled. The use of

branded credit cards and discount cards 

in stores enables retailers and marketing

companies to track every purchase and

develop spending profiles of consumers.

When information from this kind of database is added to information that can be

accessed via directories, maps, remotely

sensed imagery (e.g., aerial photos, satellite images), and various and progressively more integrated public records, anxiety

about privacy violations, real or imagined,

understandably escalates.

Crime mapping can be seen as a piece of

this privacy issue, although whether one

elects to put a sinister spin on the technology is obviously a personal decision. 

As yet, no conspicuous backlash against

crime mapping has occurred (with the

possible exception of Megan’s Law), but

whether this type of public reaction will

occur in the future is an open question.

Public access. Conflict over privacy and

access is inevitable. For every person or

group that lobbies to restrict the dissemination of crime-related information,

another lobbies to gain more access.

Surprisingly, access to crime data is still

denied to researchers on occasion.

Denying bona fide researchers access for

projects that are ostensibly in the public

interest clouds confidence in the datagathering process, since it inevitably raises questions about the reasons for denial

of access.2 As noted elsewhere, it would

seem that most crime data eventually are

released to the public through court proceedings and so on. What could be damaging and should obviously be avoided is

making unfounded data accessible to the

public (e.g., on the Web), since it carries

the accompanying risk of defaming the

innocent.

A controversial development in recent

years has been the tendency of some

States to put lists of sex offenders on the

Web, Virginia being the 10th State to do

so in late 1998. The names of more than

4,600 violent sex offenders were made

available to the public, with the effect of

“giving parents a new tool to protect their

children but also renewing fears about the

erosion of privacy in the Information Age”

(Timberg, 1998).

The names, ages, home addresses, 

conviction records, and photographs of

Virginia offenders are listed at

http://www.vsp.state.va.us, a Web site

that recorded more than 650,000 visitors

in less than 2 months after it was

135

Mapping Crime: Principle and Practice

Chapter 5
Synthesis and Applications

launched. Predictably, State officials were

enthusiastic about the site, while civil libertarians suggested that it amounted to

double punishment, with the additional

possibility that offenders’ children would

be put in jeopardy. Other potential risks

include the possibility of disseminating

false information (from computer hackers

or errors in the original files) and vigilantism. To date, registries have not been

evaluated adequately, but they are greeted

with enthusiasm by parents anxious to

protect their children.

Many law enforcement agencies have

developed Web sites displaying crime

maps (see appendix and various examples

throughout this guide). Some elect to

show crimes in the form of point data,

while others use choropleth or shade

maps. Sharp differences of opinion have

been voiced over the appropriateness of

such maps. Opponents fear negative consequences for high-crime communities;

under the worst case scenario, crime 

maps may provoke full-scale flight from

neighborhoods. Proponents tend to be

community-policing advocates who see

full disclosure of information as a tool in

crime prevention. They see Web-based

maps as community resources providing

citizens with unbiased, ready access to

crime patterns. If citizens can see where

crime is, the argument goes, they will be

better collaborators in crime prevention.

Mapping applications

for the millennium

Crime mapping can be applied to the 

following criminal justice areas: criminal

intelligence, crime prevention, courts and

corrections, public information, and

resource allocation and planning.

Criminal intelligence

Building criminal cases can be a painstaking process involving the compilation 

of information from diverse sources. All

the data have a geographic dimension,

although the importance of the locational

information varies from vital to unimportant. Spatial data may provide answers to 

obvious questions about the crime scene,

such as, Where is it?, but they also provide information for less obvious questions, such as, Where is this crime scene

in relation to other relevant persons or

objects? What locational information can

be derived from victims, offenders, and 

witnesses? Can the geographic data be

codified in the form of a map, and, if so,

would such a map be useful to investigators? Investigators might map links

between a suspect and his or her associates’ home addresses to identify where

the suspect’s daily or weekly activities

take place—the activity space. Another

possibility would involve mapping gang

graffiti as a way of defining gang territory.

Geographic analysis may be helpful on

radically differing scales. For example,

very large scale, or high-resolution, GIS

could help with representing spatial data

at crime scenes, such as the arrangement

of objects in various rooms in a house or

the pattern of crime in a highrise building

in three dimensions (for more on this, see

chapter 6). Other data may be better represented on a small scale—for example,

facts relating to suspect movements 

in other cities or states. Depending on the

136 Chapter 5
importance of spatial information, a miniatlas could be compiled, bringing together

all the known geographic information and

putting it in the context of other data.

Moland (1998) describes a case study in

crime mapping in which a “cellular phone

trail” was left by one suspect, providing

an opportunity to plot spatial and 

temporal paths of two suspects. Detectives

worked with telephone company technicians to verify that various antenna 

locations were working and to establish

various aspects of cell phone signal patterns. One of the key pieces of evidence

presented in court was figure 5.7, which

shows cell phone antenna locations associated with the suspects’ activities. This

example illustrates not only the use of

mapping to develop criminal intelligence,

but also the use of mapping to develop

courtroom evidence. The two men ultimately were convicted and sentenced to

life in prison for a gruesome murder. Maps

in the courtroom helped the prosecution

walk the jury through a complex set of

events by illustrating the collateral spatial

relationships.

The information shown in figure 5.8 could

also be used to document a pattern showing where and when incidents occurred

based on the times of the related calls for

service, as well as to provide information

to corroborate information from witnesses.

As with any new technology, the risk of

overselling GIS may lead to unrealistic

expectations and dashed hopes. The best

case scenario would include GIS as a useful contributor to the investigative process

(see also the section titled, “Geographic

profiling,” in chapter 6).

Crime prevention

In a publication titled Preventing Crime:

What Works, What Doesn’t, What’s

Promising, Sherman et al. (1998) 

document “what works” for 11 crime 

problems. They identify approximately 

30 actions or conditions as “promising.”

137

Mapping Crime: Principle and Practice

Chapter 5

Figure 5.7

A map showing key

telephone antenna

locations delineating

two suspects’ 

activity.

Source: Robert 

S. Moland, St.

Petersburg, Florida,

Police Department.

Originally published

in Moland, 1998,

figure 3. Reproduced

by permission.
Synthesis and Applications

What is interesting about these lists is that

many of the actions had little or nothing

to do with policing. Many were amenable

to the application of mapping tools,

whether they were related to crime or

other phenomena. This finding underscores that the label “crime mapping” is

much too narrow a designation for what

police departments do.

While some crime prevention actions were

in the domain of schools or social service

agencies, such as frequent visits by nurses

to the homes of mothers and infants at

risk, some were more directly connected

to policing and had locational components

that lent themselves to the application of

geographic tools:

■ Nuisance abatement action on

landlords of rental housing

plagued by drug dealing. Where are

the landlords? Where are the subject

properties? What properties does a certain landlord own across a city? Once

mapped, how can nuisance abatement

action be planned to make the best use

of both time and space resources? Can

a network analysis program be used to

optimize visits to properties?

■ Extra police patrols for high-crime

hot spots. Where are the hot spots?

How can patrol resources be optimized

so that the patrol presence is proportional to the severity of crime in the

hot spot? (Hot spots could be evaluated in terms of responses that allocate a

138 Chapter 5

Figure 5.8

A map showing a pattern of

criminal damage to property,

Overland Park, Kansas.

Source: Gerald G. Tallman,

Manager, Crime Analysis

Unit, Overland Park,

Kansas, Police Department.

Reproduced by permission.
fair share of the resources available on

a given shift.)

■ Monitoring of high-risk repeat

offenders by specialized police

patrols. Where do released repeat

offenders live? What does this pattern

look like? Can repeat offenders be categorized or prioritized by the degree of

risk they present, including the risk of

repeating and the potential severity of

the crimes they are likely to commit

based on their histories?

■ On-scene arrests for domestic

abusers who are employed or who

live in areas where most households have an employed adult.

Where are the salient locations? What

are the home and work addresses of

offenders? Can information on the 

current whereabouts of offenders and

other locational data be maintained in

a periodically updated registry?

■ Therapeutic community treatment

programs for drug-using offenders

in prison. This action recommendation

reflects the work of Harris, Huenke,

and O’Connell (1998). They used mapping to increase released offenders’

access to services in Delaware, plotting

locations of substance abuse, mental

health, employment, and other social

services, and relating them to the most

recent addresses of probationers or

parolees.

An example of a crime prevention program using geographic data in creative

ways is the autodialer system employed

by the Baltimore County Police Department

in Maryland (Canter, 1997, 1998).

Analysts subjectively identify clusters of

incidents that have similar modus operandi and occur relatively close to one another (figure 5.9). Then a GIS is used first to

randomly select telephone numbers in the

ZIP Code area coinciding with the area

under analysis, and second to further narrow down the numbers to the general area

of the crime hot spot. The autodialer then

calls all the telephone numbers on the list

with a message from the police department relaying precautions to take and

asking for reports of suspicious behavior.

Experience shows that because some displacement of crime seems to occur, target

polygons or areas must be expanded to

take this displacement into account.

Evaluation of the system suggests that it

influences the actions of the community,

the offender, and the police. Community

awareness appears to heighten (911 calls

reporting suspicious persons and vehicles

increase significantly), and crime appears

reduced, in spite of the moderate displacement effect.

Courts and corrections

Crime mapping can be applied to the 

following courts and corrections areas.

■ Probation officer service areas.

Caseload distributions can be managed

by looking at the geographic location

of probationers and parolees, and then

using a mapping program, such as the

ArcView Network Analyst, to determine the most efficient route for

sequencing visits to homes, should visits be part of the designated probation

officer’s duties. If visits to individuals

have to be made at specific times, a

route can be designed to minimize time

139

Mapping Crime: Principle and Practice

Chapter 5
Synthesis and Applications

spent traveling from one address to the

next. If time is not a factor, a route to

minimize overall travel time can be

determined (figure 5.10).

With the development of community

probation, officers are now more likely

to be assigned to small community

areas so that they have closer contact

with probationers and community

resources, including police. A program,

such as MapInfo® Redistricter, could be

used to draw (and periodically redraw)

districts based on the distribution of

caseloads. Similarly, districts could be

drawn to equalize workloads for serving warrants. Other applications in the 

probation field could include mapping

dangerous areas where probation 

officers should be accompanied by a

police officer or mapping areas that

probationers are to avoid (figure 5.11).

■ Prison location analysis. Prison

building, a booming industry in recent

decades, frequently runs into the

NIMBY (not in my back yard) problem.

Almost everyone agrees that prisons

have to be built, but few communities

(with the exception of rural locations

desperate for jobs) want them next

door. Prison location analysis is a specialized application of GIS. Location

modeling has actually been in use 

140 Chapter 5

Figure 5.9

A map showing a

residential burglary

target area before

and after autodialing.

Source: Philip Canter,

Baltimore County,

Maryland, 

Police Department.

Reproduced by 

permission.
for some time. The basic approach

involves mapping vacant and redevelopable land as possible sites for building, then adding layers for exclusions

(due to factors such as terrain, prohibited land uses, lack of utilities, and lack

of adequate transportation links) to

identify the sites with the greatest

potential for development. These sites

can then be reviewed and prioritized

with further map analysis or field

investigation.

Another locational criterion could be

the site’s distance from communities

supplying the majority of inmates.

Prisons far from their feeder communities make visitation difficult and may

fragment families. Minimizing travel

time may be a consideration not only

for families, but also for the department of corrections and the court system, because transporting prisoners 

to and from remote court offices 

will increase travel time and cost. The

accessibility of a prison to a courthouse

141

Mapping Crime: Principle and Practice

Chapter 5

Figure 5.10

A map showing a

route designed to

minimize travel time

between points 

determined by the

ArcView® Network

Analyst mapping 

program. The program can also print

street directions.

Source: Keith Harries.

Figure 5.11

A map showing 

community probation

districts mapped to

equalize workloads

using MapInfo®

Redistricter.

Source: Keith Harries.
Synthesis and Applications

can be evaluated using ArcView

Network Analyst (figure 5.12).

■ Probationer and parolee locations.

The mapping of home addresses of

parolees and probationers, along with

modus operandi data, enable law

enforcement to quickly identify local

parolees as potential perpetrators of

particular crimes occurring in a neighborhood. This type of analysis is an

integral part of the increasingly popular

ComStat (computerized statistics)

process that originated with the New

York City Police Department, in which

precinct commanders are quizzed 

regularly about crime patterns in their

areas. A big screen monitor linked to 

a GIS can immediately show parolee

locations in conjunction with offense

locations (see chapter 3). Recidivism

could also be mapped to identify hot

spots and mobilize resources necessary

to deal with the issue. Parole and probation agencies are rich in locational

information that can be used to manage caseloads, including sex offender

registries (figures 5.13 and 5.14).

■ Halfway house locations. Much like

prisons or group homes for mentally

disabled people, halfway houses provoke NIMBY reactions. Mapping demographics and housing types may help

with site selection. In an example cited

by Westerfeld (1999), a Baltimore

community needed to be persuaded

that halfway houses were appropriate

in its neighborhoods. The strategy that

was developed involved geocoding the

home locations of all Maryland prison

inmates originally from the community

in question. Maps then showed where

each inmate had lived. During community presentations, it became increasingly difficult for residents to oppose

receiving people who originally resided

in their neighborhoods.

However, publicity about the high number of escapes from halfway houses in

some jurisdictions compounds the difficulty of locating such facilities. One

solution is to seek a zoning variance 

to permit residential facilities in what

are otherwise industrial or commercial

areas. Presumably, this is a last resort. 

142 Chapter 5

Figure 5.12

A map showing

accessibility to a 

central point. 

Three zones, each

representing a 

specific travel time

are mapped using

ArcView® Network

Analyst.

Source: Keith Harries.
143

Mapping Crime: Principle and Practice

Chapter 5

Figure 5.13

An offender profile and

a draft map of offenders

in various categories.

(Details intentionally

obscured.)

Source: Eric Kim and

the Wisconsin State

Department of

Corrections. 

Reproduced by 

permission.

Figure 5.14

A draft map of

buffers around the

locations of sex 

registrants.

Source: Eric Kim

and the Wisconsin

State Department 

of Corrections.

Reproduced by 

permission.
Synthesis and Applications

A cynical solution suggests that poor,

dysfunctional communities are likely to 

be incapable of mobilizing themselves

politically so as to make the locating 

of halfway houses relatively free of

opposition.

■ Offender access to services. A

Delaware study (Harris, Huenke, and

O’Connell, 1998) analyzed the availability of rehabilitative services for

released offenders, looking at the spatial relationship between former inmate

addresses, substance abuse treatment

facilities, social service centers, mental

health services, and unemployment

offices. Nearly half of all released prisoners in Delaware return to prison within

3 years, leading to the conclusion that

postprison rehabilitation services are

inadequate, or at least inaccessible.

Maps were used to justify the implementation of drug rehabilitation 

services in Kent County and the city 

of Dover.

■ Sentence mapping. A mapping application used occasionally by court systems deals with the need to ensure fair

sentencing. Although judicial discretion

has been reduced by mandatory sentencing, it has not been eliminated

(and never will be, of course), and

substantial disparity remains in the

sentencing of similar people for similar

crimes. Like police agencies, courts

in both the State and Federal systems

have territories. The mapping of sentences is more technically challenging

than mapping crime incident data.

However, it can be done using, for

example, a weighting system that

assigns higher weights to more severe

sentences, making sure that analysis

of offender characteristics and crime

types is properly controlled for. (For

details on this concept and examples of

geographic analyses of sentencing, see

Harries and Lura, 1974, and Harries

and Brunn, 1978. For a discussion of

geographic issues specifically relating

to capital sentencing, see Harries and

Cheatwood, 1997.)

■ Courtroom presentation. As noted 

in the discussion of figure 5.7, maps

showing sequences of events and patterns can be used in court to provide

an easily comprehended visual rendition of a criminal process. Such presentations may be constructed on any

scale, from international drug trafficking to the layout of a murder scene in

one room of a building. In figure 5.15,

the information on a sequence of

events involving sexual torture and

hostage taking was mapped to provide

the prosecution with a plausible

chronology of events that could be

readily communicated to judge and

jury.

Public information

“Public information” is a phrase that

evokes mixed emotions in police departments. Some make vast amounts of data

readily accessible to the public through

the Web, while others are reluctant to

have a Web site at all, let alone include

crime data on it. At the risk of stereotyping, it could be suggested that the more

defensive posture tends to reflect “old

school” thinking, whereas willingness to

share data represents a more contemporary,

“let the light shine in” approach, consistent with community policing values.

144 Chapter 5
Even the most avid proponents of data

access would concede that cases with

ongoing investigations should be exempt

for obvious reasons. However, beyond

active cases and cases involving rape victims and juveniles, active concealment is

difficult to justify. From a public policy

perspective, one of the strongest justifications for open data access is that it makes

putting a “political spin” on things somewhat more difficult. Every agency, at

every level of government, wants to make

itself look good, and to this end information is power. Limit information dissemination and the power of the opposition is

crimped.

Some public constituencies also prefer to

suppress crime data, and particularly crime

mapping data, from public view for fear

that their investments will be negatively

affected. Such considerations seem of 

particular concern to realtors and some

property owner’s associations. The rationale is that any publicity about crime tends

to depress property values. But what is

overlooked is that publicity about crime

may draw more attention to the problem

with the possibility of remedial action. In

this context, the possibility of long-term

gain is sacrificed for short-term expediency.

The more prevalent perspective today is

that an informed public can best assist

law enforcement, given that police cannot

be in all places at all times, and that policing will be most effective when it is performed in an environment in which the

public offers active support. Clearly, maps

are tools that can assist in this effort

through their use at community meetings

and their distribution to the media, 

citizen patrols, and neighborhood groups.

However, maps must be tailored to each

group, and a poorly designed or poorly

presented map may do more harm than

145

Mapping Crime: Principle and Practice

Chapter 5

Figure 5.15

An example of a map

used in court in

Overland Park, Kansas,

to substantiate the

times the victim reported she was in certain

places. The victim’s

address and other

details have been 

modified or erased to

protect the privacy of 

the victim in this case.

Source: Susan

Wernicke, Overland

Park, Kansas, 

Police Department.

Adapted by permission.
Synthesis and Applications

good by creating confusion where none

may have existed before.

Internet media offer public information

opportunities that go beyond merely having a Web site or providing maps. The

Web also offers opportunities for feedback

from the public via survey forms that

solicit information about specific crimes or

problem areas and neighborhood-specific

bulletins. A review of police department

Web sites linked through the Crime

Mapping Research Center Web site (see

appendix) demonstrates some of the

many possibilities.

Resource allocation

and planning

As noted in chapter 3, the fundamental

principle behind resource allocation is the

efficient assignment of valuable resources.

In theory, at least, more resources should

be assigned to areas where crime is most

prevalent. It was suggested in chapter 3

that calls for service be used as either a

crude or weighted index to help determine

the allocation of patrol resources on a pershift basis. A choropleth map of neighborhoods classified by their levels of CFS

could be the tool used for planning

resource allocation.

In a community policing context, this

approach can be expanded by looking not

only at the calls for service themselves,

but at the local social conditions associated with high levels of CFS. This not only

forms a foundation for planning direct law

enforcement strategies, but also sets the

scene for cooperation with other criminal

justice system agencies and social service

agencies. An example of this approach,

applied in Cincinnati, is shown in figure

5.16. The choropleth map of calls for

service by neighborhood and analysis of

social indicators showed that the prevalence of nonowner-occupied housing was

the strongest social correlate of CFS levels.

Models that relate social conditions to 

levels of crime or CFS take many different

forms, and examples can be found in the

literature on the social ecology and geography of crime (Felson, 1998; Byrne and

Sampson, 1986; Harries and Powell,

1994; Harries, 1995; Taub, Taylor, and

Dunham, 1984; Bursik and Grasmick,

1993; and Rose and McClain, 1990).

Crime analysis 

and the census

Postings on the Crime Mapping Research

Center’s listserv indicate that the manipulation of census data is a confusing obstacle

for many analysts. This is not surprising,

since census data and census geography

are somewhat complex, or can be,

depending on what you are trying to do.

Among the most problematic areas are

linking census geographies to data and

misunderstandings relating to what can

reasonably be, and not be, done with 

specific census “counts” and variables.

For example, what measure of income

should be used? The census contains data

on family income and household income.

Families are subsets of households, so

these data for families exclude single 

persons living alone or unrelated persons

living together (who constitute households). Family income will be higher than

household income because the average

family has more wage earners than 

the average household. Normally, because

146 Chapter 5
it is more inclusive, the preferred measure

is household income.

A second question arises: Is it best to use

median income or mean income? The

mean has the advantage of being able to

be manipulated mathematically, but in a

skewed distribution, such as is found with

income, the mean may be “pulled” to 

the right by the very high values of the

extremely rich (the so-called Bill Gates

Effect!). For such skewed distributions,

the median is usually preferred since it

gives a more accurate description.

Detailed treatment of these questions is

beyond the scope of this guide. An excellent review of issues in census geography

and the analysis of change using census

data can be found in Myers (1992).

Conclusion

Mapping criminal justice elements is well

advanced, although unevenly distributed

among police agencies. Most applications

are horizontal, which is to say within the

various levels of the criminal justice system. The real challenge is to integrate

mapping applications vertically, so that

agencies can be linked according to specific problems and be regionally integrated.

This is a tall order given the political insularity of agencies and turf and control

issues. The perfect world of analysis and

mapping might look something like table

5.1. Ideally, mapping applications would

be integrated to permit automated multistep analyses. Quite apart from political

impediments to data integration, technical

obstacles can make integrated analysis

147

Mapping Crime: Principle and Practice

Chapter 5

Figure 5.16

(Top) A map showing

calls for service in

1997 per 1,000 people

by neighborhood in

Cincinnati, Ohio.

(Bottom) A map

showing nonowneroccupied housing,

which can be used as

an index of possible

social disorganization.

Sources: Shape files

and analysis by 

A. Ball, COPS 

Regional Institute, 

and M. Neumann,

Cincinnati, Ohio,

Police Department.

Adapted by permission.
Synthesis and Applications

quite cumbersome because many spatial

joins, which link databases according to

their geography, are needed to indicate

how records relate to geographic areas.

Summary

Chapter 5 has explained:

■ The characteristics of crime mapping

for the new millennium.

■ How crime mapping can be applied to:

■ Criminal intelligence.

■ Crime prevention.

■ Courts and corrections.

■ Public information.

■ Resource allocation and planning.

■ Where to obtain a better understanding

of census geography and analysis.

■ How crime mapping applications 

could be broadened to improve their

effectiveness.

Notes

1. Personal communication from Michael

Ratcliffe, U.S. Census Bureau, Population

Division, January 25, 1999.

2. While most law enforcement-academic

collaborations are amicable and productive, this is not always the case owing to

the vagaries of human nature that occasionally leave either or both parties feeling

used and abused. As in other relationships, the key to success seems to be the

unsurprising revelation that all parties

should be sensitive to the others and

avoid exploitive actions.

148 Chapter 5

Table 5.1. Horizontal and vertical linkages in analysis and 

mapping among criminal justice entities 

Agencies Current Mode Ideal Mode + Region

Law Independent 

enforcement analysis

Courts Independent 

analysis

Corrections Independent 

analysis

Source: Keith Harries.
149

Mapping Crime: Principle and Practice

Chapter 5

What’s Next in Chapter 6?

■ Types of changes that may be expected in the next decade.

■ Geographic profiling.

■ High-resolution GIS. 

■ The use of complex statistical methods in spatial forecasting. 

■ Aerial photography.

■ How various kinds of data visualization can be integrated productively. 

■ GIS and global positioning systems (GPS).

■ The possibility of limits to data access.

■ Applications of multimedia and integration technologies.
151

Mapping Crime: Principle and Practice

Chapter 6

Chapter 6:

Crime Mapping

Futures

Applications in crime mapping are becoming increasingly sophisticated and integrated. The hallmark of the

first decade or so of the modern era of crime mapping

was the use of geographic information systems (GIS).

Perhaps the next decade will see the integration of

previously separate technologies such as global positioning systems (GPS), orthophotography, digital photography, digital videography, and a wide range of

local databases with relevance to policing—and the

World Wide Web. Another realm of potential progress

lies in forecasting. A remarkable indication of the level

of interest in crime mapping and related technologies

was contained in President Clinton’s State of the

Union Address on January 19, 1999, in which he said:

Tonight, I propose a 21st century Crime Bill to

deploy the latest technologies and tactics . . . 

[to] put up to 50,000 more police on the street 

in the areas hardest hit by crime, and then to

equip them with new tools—from crimemapping computers to digital mug shots.

[Emphasis added.] 

While it is not possible to explain or even identify all

the innovative crime mapping applications in the field

or under development, the following are outlined below

to provide a sense of the kinds of methods and technologies that are likely to find increasing acceptance
Crime Mapping Futures

in the years ahead: geographic profiling,

which has already found wide recognition

and is representative of a method that creatively combines various tools of spatial

analysis; high-resolution GIS; statistical

methods and forecasting; digital aerial

photography; and the integration of GIS

and GPS.

Geographic profiling1

Geographic profiling is an investigative

methodology that uses the locations of 

a connected series of crimes to determine

the most probable area that an offender

lives in. Although it is generally applied in 

serial murder, rape, arson, robbery, and

bombing cases, geographic profiling also

can be used in single crimes that involve

multiple scenes or other significant geographic characteristics.

Developed from research conducted at

Simon Fraser University’s School of

Criminology and rooted in the pathbreaking

work of Brantingham and Brantingham

(1981), the methodology is based on a

model that describes the hunting behavior

of the offender. The criminal geographic

targeting (CGT) program uses overlapping

distance-decay functions centered on 

each crime location to produce jeopardy

surfaces—three-dimensional probability 

surfaces that indicate the area where 

the offender probably lives. The distancedecay concept (see chapter 1) conveys the

idea that people, including criminals, generally take more short trips and fewer long

trips in the course of their daily lives, which

may include criminal activities. Thus 

overlapping distance-decay functions are

sets of curves expressing this phenomenon and suggesting, for example, that it 

is more likely that offenders live close to 

the sites of their crimes than far away.

Probability surfaces can be displayed on

both two- and three-dimensional color

isopleth maps, which then provide a focus

for investigative efforts (see chapter 1 for a

description of isopleth maps).

This research has led to the development

of Rigel, a computerized geographic profiling workstation that incorporates an analytic engine, GIS capability, database

management, and powerful visualization

tools. Crime locations, which are broken

down by type (e.g., victim encounter,

murder, and body dump sites for a murder),

are entered by address, latitude/longitude,

or digitization. Scenarios wherein crime

locations are weighted based on certain

theoretical and methodological principles

are created next and examined. The

addresses of suspects can then be evaluated according to their “hit” percentage on 

a probability chart known as a z-score

histogram, which can prioritize registered

sex offenders, other known criminals, task

force tips, and other information contained

in databases.

Geographic profiling can be used as the

basis for several investigative strategies.

Some of the more common ones include: 

■ Suspect and tip prioritization.

■ Address-based searches of police

record systems.

■ Patrol saturation and surveillance.

■ Canvasses and searches.

■ Mass DNA screening prioritization.

152 Chapter 6
■ Department of motor vehicles searches.

■ ZIP Code prioritization.

■ Information request mailouts.

Figure 6.1 displays the geoprofile produced

from the analysis of 32 armed robberies

that occurred over a period of approximately

12 months in the city of Vancouver,

British Columbia, Canada. The purple

areas around the periphery are less likely

to include offenders’ residences, and the

yellow and orange areas in the center 

are more likely to include offenders’ residences. Three strategies were predicated

on the geographic profile in this case.

First, a search was conducted of the

Vancouver Police Department’s Records

Management System for known robbery

offenders who matched the criminals’

descriptions and resided within the top 5

percent of geographic areas identified in

the geoprofile. This did not produce any

viable matches, as neither offender had

had a previous conviction for robbery.

Second, a simplified geoprofile, displaying

only the top 2 percent (0.7 square miles)

of potential offender residences, was produced for patrol officers. Previous research

determined that robbery offenders usually

return home after committing a crime. It

was therefore suggested that, in addition

to responding to a crime scene after the

report of a new robbery, patrol members

should also search the most likely area

of offender residence, paying particular

attention to logical routes of travel. This

also was unsuccessful as the offenders

were using stolen cars and no reliable

vehicle descriptions were ever obtained

(even though the geoprofile was used by

police units to search for stolen automobiles that might be abandoned prior to a

new robbery). 

Third, the results of the geoprofile

were released on the television show

“CrimeStoppers.” This approach was successful, producing results that allowed the

detectives to identify the offenders responsible for the series of robberies. The primary

153

Mapping Crime: Principle and Practice

Chapter 6

Figure 6.1

A geoprofile of 

a series of armed

robberies in

Vancouver, British

Columbia, Canada.

Source: Det. Insp. 

D. Kim Rossmo,

Vancouver, 

British Columbia,

Police Department.

Reproduced by 

permission.
Crime Mapping Futures

offender’s address was located within 

the top 1 percent of the peak area of 

the geoprofile.

It is important to stress that geographic

profiling does not solve cases, but rather

provides a means for managing the large

volume of information typically generated

in major crime investigations. It should be

regarded as one of several powerful decision support tools available to the detective and is best employed in conjunction

with other police methods. Geographic

crime patterns are clues that, when properly decoded, can be used to point in the

direction of the offender.2

Currently, geographic profiling services 

are available from the Vancouver Police

Department, Geographic Profiling Section,

Vancouver, British Columbia, Canada; the

Royal Canadian Mounted Police, Pacific

Region ViCLAS Section, also in Vancouver;

and the Ontario Provincial Police,

Behavioral Sciences Section, Orillia,

Ontario, Canada. It will be available in 

the near future from the British National

Crime Faculty, Bramshill, United Kingdom.

Concerned about the mapping and prediction of serial crimes, Geggie (1998)

reported on the work of Officer Timothy

Meicher of the Los Angeles Police

Department. The case related to robberies

involving a perpetrator who rode a motorcycle and snatched purses from elderly

victims in shopping center parking 

lots—hence the title “the Los Angeles

Motorcycle Bandit.” Employing basic 

statistical concepts—mean and standard

deviation—Meicher produced a map with

boundaries indicating two probability 

levels for the next bandit strike, one at 

68 percent and the other at 95 percent

(figure 6.2). Meicher then collaborated

with Geggie to automate the process of

producing the probability map. Their

model was subsequently distributed both

inside and outside the Los Angeles Police

Department.

154 Chapter 6

Figure 6.2

A map showing

probability boundaries in the 

Los Angeles,

California,

Motorcycle Bandit

case.

Source: Geggie,

1998. Reproduced

by permission.
High-resolution GIS

We often lose sight of the fact that GIS

can be useful on any geographic scale,

from global (small scale) to small (large

scale), such as a room. Most crime analysis is conducted on what could be labeled

medium scale, typically representing a city

or neighborhoods within a city. Rengert,

Mattson, and Henderson (1998) have

reported on GIS applied to individual

buildings or other small areas, such as

street segments, terming this approach

high-resolution GIS. The four panels of

figure 6.3 contain several views representative of this approach. In the upper left

panel, a “plan” view shows the footprint

of a highrise building on the Temple

University campus in Philadelphia. Crime

incidents have been compressed so that

they are all seen as if at one level. This

compression enables law enforcement to

determine whether incidents might be

clustered around elevator shafts, for

example, or restrooms, which tend to be

at identical locations on each floor of a

highrise. The upper right panel provides a

perspective of the building with incident

locations in their three-dimensional positions. At lower left, a technique for delineating clusters uses spheres to provide a

sense of what might be called “highrise

hot spots.” Then at lower right, a cluster

within a cluster defines the limits of the

larger pattern of incidents and then focuses on the denser pattern within.

Forecasting: Complex

statistical methods and

crime mapping 

In cooperation with the Pittsburgh Police

Department, Olligschlaeger (1997) employed

advanced statistical methods in an attempt

to identify emerging drug markets, which

155

Mapping Crime: Principle and Practice

Chapter 6

Figure 6.3

A map using highresolution GIS to

show crime in a

highrise building.

Source: Rengert,

Mattson, and

Henderson, 1998.

Reproduced by 

permission.
Crime Mapping Futures

are relatively difficult to detect by conventional means. This is because they often

are revealed only indirectly through the

commission of other crimes, such as robberies or burglaries, and then only after a

delay. Given the importance of drug markets as crime generators, early warning 

is useful. Three types of calls for service

(CFS) were used to develop models:

weapon-related, robbery, and assault.

Commercial land use and seasonality

were also included as model criteria based

on evidence in the literature. A grid of

cells measuring 2,150 square feet was

then superimposed on the city, with the

size of the cells determined by the need to

have cells big enough to represent a reasonable number of CFS, but small enough

to supply an adequate number to satisfy

statistical modeling requirements. The grids

were then used as the framework for choropleth maps.

Following rules based on gaming simulation, a statistical model estimated the consequences of the various types of CFS at

certain levels. (For details of the model’s

architecture and specifications, see

Olligschlaeger, 1997). Then forecasts 

from different methods were compared

with actual patterns to provide a basis for

evaluation.

Experience showed that a type of gaming

simulation model known as the neural

model did better than other types tested.

A difficulty with the analysis—namely, 

the use of large quantities of computer

resources—becomes less of a problem as

the power of personal computer processors

increases. Overall, the analysis suggested

that advanced methods of the type tested—the neural model—could be useful

tools in spatial forecasting.

Mapping change: 

From pins to grids

Also employing a grid mode of representation for Pittsburgh, Gorr used 750-foot

cells approximating four city blocks. Based

on a pin map, a grid map (figure 6.4) 

156 Chapter 6

Figure 6.4

A map of grid

cells. Reproduced

by permission.

Source: Wilpen

Gorr, Heinz

School of Public

Policy and

Management,

Carnegie Mellon

University,

Pittsburgh,

Pennsylvania.

Reproduced by

permission.
displays the Part I crimes from the pin

map in each grid cell, suppressing cells

with only one crime. The grids show the

total demand for serious crime suppression, in combination with an indicator of

crime-prone land uses. The latter indicator 

came from the PhoneDisc®3 yellow pages

and includes the total number of restaurants, fast-food stands, bars, drug stores,

retail stores, pawn shops, jewelry stores,

etc., by grid cell, suppressing cells with

only one such establishment. This example shows how the reformulation of information and the introduction of a related

layer (or layers) of data can provide new

and more useful interpretations than the

original data alone.

As shown in figure 6.5, this methodology

was used to analyze change by converting the two pin maps into grids and then

subtracting one from the other to get the

measure of change. Grid cells have several

advantages:

■ They clearly show crime intensity in

places with many overlapping point

markers.

■ Their data are in the form needed for

time-series plots, bar charts, and statistical analyses, which are examples of

crime space/time series, with one

“slice” shown in figure 6.5.

157

Mapping Crime: Principle and Practice

Chapter 6

Figure 6.5

Two pin maps and a

change map for August–

September 1998, based on

pin maps of Part I crimes

for Pittsburgh Police Zone

2 (the equivalent to a

precinct). The pin maps

include streets and car

beats for the zone, as well

as downtown Pittsburgh,

Pennsylvania, (the two

beats on the left) and 

several neighborhoods.

Source: Wilpen Gorr,

Heinz School of Public

Policy and Management,

Carnegie Mellon

University, Pittsburgh,

Pennsylvania. Reproduced

by permission.
Crime Mapping Futures

■ The grids can be used to produce

change maps that are more legible

than pin maps.

Making maps come to life4

Application of Virtual Reality Modeling

Language (VRML) to crime data allows

the user to change a viewpoint by rotating, translating, zooming in and out, and

tilting maps, providing a dynamic way of

viewing crime. The images shown in figures

6.6 and 6.7 are part of an animation

that depicts different crime types reported

to police for various time periods in

Vancouver, British Columbia, Canada. In

158 Chapter 6

Figure 6.6

A rotated view of

six types of crimes

on a map of

Vancouver, British

Columbia, Canada.

Different crime

types are mapped

to different colors

and stacked in

three dimensions.

Source: Lodha and

Verma, 1999.

Reproduced by

permission.

Figure 6.7

A zoomed-in view

of six types of

crimes on a map of

Vancouver, British

Columbia, Canada.

Source: Lodha and

Verma, 1999.

Reproduced by

permission.
its original context, this animation could

be activated by clicking the start button

shown in the images. The process of creating the images involves first rasterizing

the data, then developing a color code key

for the crime types, and, finally, designing

a system for displaying the crime—in this

case, as a histogram.

In figures 6.6 and 6.7, six different types

of crime are illustrated: assault (ASLT),

breaking and entering (BNE), family trouble (FAMTRB), mischief (MSCHF), auto

theft (TFAUTO), and theft (THEFT). The

height of the stack is proportional to the

total number of crimes in an area, so hot

spots can be recognized as “highrises.”

The two figures display the same data—

the same map—from different viewpoints

after rotating and zooming in.

Another approach that is easy and yet

quite effective as a means of visualizing

change involves animating a two-dimensional map. In figure 6.8, calls for service

in Mesa, Arizona, were mapped and (in the

original) animated. This map uses isoline

mapping (joining points of equal value—

in this case, equal CFS counts5). The animation is a rapid-sequence display of a

series of maps of successive arbitrary time

intervals giving the visual impression of

movement, much like an animated cartoon.

These applications illustrate how we can

expect maps to become more dynamic,

more maneuverable, in the years ahead.

Not only is it likely that the flexibility 

of maps will improve, but a more userfriendly environment will likely evolve in

parallel. The average analyst will simply

not have time to do the programming that

Lodha and Verma (1999) did to produce

their maps, and tools of this sort will, of

necessity, become easier to use.

Digital aerial 

photography in policing

As noted throughout this guide, police

departments employ GIS technology in

various applications, including criminal

159

Mapping Crime: Principle and Practice

Chapter 6

Figure 6.8

A map showing the

density of police

calls for service in

the first quarter of

1999 in Mesa,

Arizona.

Source: J. Werner

and the Crime

Analysis Unit, 

Mesa, Arizona,

Police Department.

Reproduced by 

permission.
Crime Mapping Futures

intelligence and crime analysis, crime prevention, public information, and community policing. Typical GIS applications

involve taking a georeferenced crime 

database, filtering the data as needed, and

mapping it over a street database to put the

crime data in its spatial context. Other data

layers may be used, such as census tracts,

ZIP Codes, or council districts, but the

most frequent underlying context is city

streets.

Digital street maps typically provide

extremely limited contextual information.

Streets are represented as single lines and

sometimes color coded to indicate their

type (e.g., freeway, arterial, collector).

They can be labeled, if necessary, to

enhance the level of detail, but the information provided by the street database is

quite limited. In recent years it has become

clear that the visualization of crime data

needs to be improved to provide opportunities for better communication within and

between the internal and external constituencies of police departments. 

We can portray the general context of

visualization along a continuum from

complete abstraction, at one extreme, 

to reality at the other (figure 6.9). Most

existing crime maps would be located left

of center on the continuum. The crime

mapping future will see increasing movement to the right, toward more realistic

presentations. 

Confidentiality and privacy considerations

will probably set limits on how far to the

right the process moves. Ultimately, these

limits will be culturally conditioned, with

more detail where public information and

geographic precision are prized and less

detail where values put more emphasis on

privacy. This variation will be seen, and 

is already seen, from city to city, State to

State, and nation to nation.

Increasingly, police departments are using

large-scale (representative fraction

1:2,400) digital aerial orthophotos, also

known as DOQ, for digital orthophoto

quadrangles. The “ortho” part means 

160 Chapter 6

Figure 6.9

A diagram

illustrating the

abstractionreality 

continuum.

Source: Keith

Harries. 
perpendicular to the Earth’s surface, just

as orthodontics corrects teeth so that they

are perpendicular to gums. Photos are produced in “tiles,” or rectangles, such that

each tile typically represents about a

square mile (4,000 feet by 6,000 feet or

24 million square feet6). The tiles are 

rectified for errors due to edge distortion

(which increases away from the camera

lens), other distortions due to the attitude

(or position) of the airplane, and terrain.

The edges of the tiles must match perfectly. The raster images (see chapter 4) are 

registered to the center lines of the appropriate digital street-based maps so that

geocoded crime data can be accurately

portrayed in their “real” spatial context, 

permitting the identification of land uses,

landmarks, and virtually any relevant

landscape features. 

Furthermore, other coverages are typically

digitized and made available as part of 

the orthophoto package, including spot

heights, building footprints, topography,

street boundaries, water bodies, and open

space. These can be quite useful with or

without the associated orthophoto. The

data within the photos and the associated

digitized coverages are so rich that they

could find applications in tactical team

operations, for example, where land elevation, terrain, building heights, building

footprints, fences, and water bodies can be

used to plan where to place officers and

determine what their sight lines will be. 

While maps have progressed from two

dimensions to three, so have aerial photos. Just as three-dimensional maps have

limited specialized applications, the applications of three-dimensional photos are

likewise limited at present, but potential

uses are numerous and ultimately limited

only by the user’s imagination. As the

example in figure 6.10 shows, images can

be quite striking in their depth and realism

and add to the crime analyst’s arsenal of

environmental data.

Potential applications of aerial photography are numerous. Any geocoded 

161

Mapping Crime: Principle and Practice

Chapter 6

Figure 6.10

A three-dimensional

orthophoto cityscape.

Source: Orthophoto

imagery and 

three-dimensional

model courtesy of 

ASDI Technologies, 

Colorado Springs,

Colorado. 

Reproduced by 

permission. 
Crime Mapping Futures

information can be superimposed on the

photos, including census data, liquor

license locations, drug-market data, injury

locations, probationer addresses, housing

and zoning code violations, and other

data that may be relevant to the needs 

of community policing (see, for example,

figure 4.4 in chapter 4). Eventually, we

may see orthophotos supplanting “traditional” street-based maps in some, if not

all, of the applications where such maps

have typically been used.

Integration of orthophotos with conventional data is by no means the only possibility for enhanced visual display. For

example, other raster images may be

keyed to the orthophotos. One possibility

explored in a pilot project7 in Baltimore

County, Maryland, was the development

of an archive of ground-level digital photos

intended to characterize neighborhoods

and landmarks, precinct by precinct.

These ground-level images were linked to

a land use map database, and symbols

were placed on the land use map at all

locations where a ground-level photo had

been taken. In ArcView®, hot links were

established between the symbols and the

database; when the symbols were clicked

on, the ground-level picture would pop

up, as shown in figure 6.11 (for specific

directions, see ESRI, Inc., 1997, chapter

16, “Creating Hot Links”). Yet another

possibility is the use of virtual reality to

enhance the visualization of scenes in a

way that provides somewhat more flexibility than an analog videotape. A set of

digital photos is taken in a circle using a

special tripod, with the number of pictures

calibrated to the focal length of the camera lens. Then a program is used to splice

the pictures together at the edges. A 

viewer with pan and zoom capabilities

enables re-creation of the 360-degree

panorama. Free viewers are available for

162 Chapter 6

Figure 6.11

A ground-level 

photograph that pops

up when linked to a

land use map in

ArcView®.

Source: Keith Harries. 
downloading (see appendix). This technology could be used for training purposes, for documenting a crime scene that

could serve as evidence in court, or for

community meetings when a specific location may be the focal point of interest 

(figure 6.12).

The 360-degree view provides a sense of

the local environment that may not be

conveyed by either a ground-level still

picture or an orthophoto. Virtual reality

presentations could be linked to maps or

orthos, too. To get a sense of what virtual

reality is like, go the National Gallery of Art

Web site (http://www.nga.gov/home.htm),

where virtual reality tours are available

(see appendix).

Until recently, the costs of storage and

random access memory (RAM) limited 

the use of memory-intensive applications,

such as the display of orthophotos. Each

tile, with its associated coverages, requires

about 30 megabytes of hard drive space. 

A city like Baltimore or Washington, D.C.,

each somewhat less than 100 square

miles, would need more than 3 gigabytes

(GB) dedicated to it. But with hard drives

of 20+ GB readily available at modest

cost, this limitation no longer poses a

problem. Likewise, the relatively low cost

of RAM permits the fast manipulation of

large graphics files.

Anticipated applications of orthophotos in

community policing include:

■ Community residents being able to

select their homes or apartment buildings and seeing how the locations of

crime incidents or other illicit activities

relate to their own locations even if

they have no firsthand experience of

the events.

■ Officers more easily recognizing and

contextualizing information, whether

that information involves crime locations or various social or environmental problems.

■ Police dispatchers (who are increasingly likely to be civilians relatively unfamiliar with the detailed community

geography of the city) having the

capability to enrich dispatching information with landmarks as reference

163

Mapping Crime: Principle and Practice

Chapter 6

Figure 6.12

A 360-degree panorama

(top), and a selected

part (bottom), of

interest owing to

the potential conflict

between public housing

and owner-occupied

housing residents. 

A wall was built to

separate the two

“neighborhoods.”

Source: Keith Harries

and Thomas

Rabenhorst.
Crime Mapping Futures

points provided by photos that pop up

on their computer screens. Dispatching

technology could be enhanced dramatically if both dispatchers and officers in

the field could simultaneously see

orthophotographic images displaying

the origins of calls.

■ Crime prevention officers, analysts,

commanders, and administrators being

able to present more persuasive visual

evidence of problems and communicate

better with legislative bodies, community

groups, and their professional colleagues.

■ Planning being enhanced by realistic

and accurate perceptions of the size

and scope of proposed actions.

The integration

of GIS and GPS

The integration of data and technologies

will be pushed to the limit to extract as

much value as possible. The possibilities

are limited only by our imaginations.

Whereas GIS offers a powerful toolbox,

GPS, another technology with untapped

potential in law enforcement, permits

accurate location finding in field settings.

Triangulating from 24 satellites (put in

orbit at a cost of $12 billion by the U.S.

Air Force), GPS, in its more advanced

modes, can provide accuracy to one 

centimeter, or about half an inch. (For a 

tutorial explaining how GPS works, go to

http://www.trimble.com.) 

In reality, however, structural and environmental limitations, such as tall buildings, a forest canopy, or operations in

mountainous terrain, and the ability of 

the Air Force to manipulate the accuracy

available to civilians may mean an error

of up to 100 meters. These problems can

be overcome by using GPS base stations

with established locations and manipulations that have come to be referred to as

differential positioning GPS or DGPS. This

is defined by GPS World Magazine as: 

A technique used to improve positioning or navigation accuracy by determining the positioning error at a

known location and subsequently

incorporating a corrective factor (by

real-time transmission of corrections

or by postprocessing) into the 

position calculations of another 

receiver operating in the same area

and simultaneously tracking the 

same satellites. 

The bottom line, however, is that users

should generally be prepared for considerably lower resolution than some numbers

quoted in promotional materials.

Another possibility for integrating technologies involves the combined use of

GIS, GPS, and management information

systems (MIS). This would allow close 

to real-time crime mapping, since the

geocoding step would be eliminated

(Sorensen, 1997). However, some operational questions need to be examined. For

example, with how much certainty will

incident locations be reported? A patrol

officer may report “arrived” status prematurely, sending what in theory should be

the incident location, but what in practice

may be erroneous. On the other hand,

GPS offers the possibility of accurately

reporting places that have no meaningful

street address. A shopping mall covering

100 acres may have a conventional street

164 Chapter 6
address that is meaningless in terms of

conveying locational precision. With GPS,

the precise spot of an auto theft in the

parking lot could be pinpointed, providing

potentially useful information for protecting areas of the parking lot that are prone

to theft. Crime inside the mall building

could be reported with greater precision,

whether in stores or in public spaces, provided a reasonably close line-of-sight GPS

reading could be obtained. This type of

“precision mapping” is already being performed in Charlotte, North Carolina, where

GPS is used to plot exactly where crimes

occur, even for locations without street

addresses.

An application of GPS that is in development is in the area of probation and

parole—tracking probationers and parolees

if the terms of their release require limitations on their mobility. Indeed, future

crime mapping applications will go beyond

crime mapping per se and into other components of the criminal justice system,

including corrections. One can expect to

see the manipulation of spatial information and the application of new tools and

technologies evolving in the coming

decade. While developments in other

branches of criminal justice will likely 

parallel spatial analysis developments in

policing, we also can expect to see the

development of specialized methods

adapted to particular needs.

Postscript: The future 

of GIS in policing

When asked, “Why bother to discuss the

future of GIS?,” Clarke (1997) responded

with three reasons that might apply

equally to crime mapping: 

■ The need to plan equipment purchases

in the most efficient way, anticipating

trends.

■ The need to stay abreast of the new

field spawned by GIS called geographic

information science.

■ The need to be prepared for crossfertilization of different criminal justice

fields using GIS.

Clarke suggested that we can classify

speculation into two types: 

■ The forward extension of current trends.

■ Pure speculation, with the likelihood

that some ideas will become reality

while others will fade away.

Clarke also noted that data will become

more complete, more detailed, more timely, and more varied than ever before. This

will be helpful to GIS as an “end user” 

of data—if the core data get richer, then

possibilities for enhanced analysis also

increase. But Clarke was referring to GIS

in general. Can we have the same expectations for crime mapping? 

Given that most crime data are already

point defined (address-type), could they 

be improved in terms of spatial definition?

Yes, at least marginally, through the use

of GPS technology to remove address

ambiguities, of which there are many.

Whether locational data can be improved

across the board may depend on the GPS

protocols that develop, one police department at a time. Data quality will probably

improve, and addresses will probably

become more precise as more agencies use

automated field reporting and integrated

165

Mapping Crime: Principle and Practice

Chapter 6
Crime Mapping Futures

computer-assisted dispatching and records

management systems.

More on GPS and policing

Equipping patrol units with GPS would

mean that their locations could be known

as often as each unit is “polled,” or automatically asked to respond, perhaps every

few minutes. This would be an excellent

security device for officers, since their

location could be determined at any time,

and, if an officer were down or needed

help, knowing his or her location would

save valuable time.

But will GPS units typically be located 

in patrol cars? If so, some ambiguities in

incident location will remain, since the car

will not always be parked precisely where

the incident takes place. If GPS units are

hand held, or incorporated into officers’

uniforms, accuracy may improve significantly. The caveat on GPS data, however,

is that the physical environment may not

permit a satellite reading owing to the

presence of tall buildings or other obstacles. Such difficulties aside, the era of realtime access to spatially enabled crime data

is rapidly approaching—a development

that will force us to reconsider what we

are doing and why and how we are doing

it. This development is not without risks,

such as the temptation to jump to premature conclusions on the basis of real-time,

but possibly unconfirmed, information. 

The Web: Already a force 

in the dissemination of 

police information

A development that may have the greatest impact on the manipulation of crime

data may be the use of the Web for access

to data that have already been geocoded

and are in the public domain, such as 

census data, including census geography. 

A corollary development will likely be

demands for local data on Web sites.

Currently, police departments are split on

this issue, with some routinely putting

their less sensitive data on the Web, and

others refraining from doing so. The

power of the Web to facilitate data sharing

will invite more open data dissemination

protocols, but these will be offset to some

extent by security and privacy concerns.

Public information revisited:

How much public access to

allow

A pervasive force at work in the background is the historical culture of policing

that has generally frowned on easy public

access to crime data. This reluctance is

borne of several factors, including fear of

misuse and misinterpretation; the indisputable need for confidentiality for some

crimes, such as rape and juvenile offenses;

fear of political reprisals when crime rates

are increasing; and a reluctance to expend

scarce resources on data dissemination. 

In the background was, and is, a certain

degree of proprietorship regarding data and

a somewhat natural reluctance to simply

give information away, even though it

might be in the public domain already, at

least in theory. A subtext to this is the

view that crime data should not be made

available to the public if they do not have

to be, since public disclosure only constitutes another potential source of problems. 

On the other hand, undermining nondisclosure is the fact that many city and

166 Chapter 6
neighborhood newspapers routinely publish lists of local crimes, complete with

addresses. The only missing link is the

codification necessary to produce a citywide map. Criminal matters most often

come before the courts and, in so doing,

jump squarely into the public domain. In

the long term, it is increasingly difficult to

see how most crime data could be kept

private, particularly data related to incidents for which there is no active investigative interest and no need to protect

victims. Indeed, some departments that

were secretive a decade ago are now

beginning to put their data out on CDROMs or at least are talking about doing

so. Others refuse to release data, even for

legitimate apolitical research.

One certainty is that, in addition to technological and methodological innovations

in crime mapping and in collateral fields

that can be productively integrated into

mapping methods, a debate about the disclosure and exposure of crime data will

continue into the foreseeable future. 

Multimedia and integration

Multimedia and integration are likely to be

among the most prominent themes that

evolve in the crime mapping arena over

the next decade. Crime mappers will 

certainly take advantage of all the new

technological advances, often using multimedia in ways that their developers might

not have anticipated. Integration of various technologies, with data archiving (or

warehousing) and data mining becoming

more prominent, will be inevitable. Crime

mapping may find itself merging into an

enterprisewide GIS, as governments network access to data and standardize GIS

platforms across entire jurisdictions to

ensure compatibility and reduce costs.

Change is certain. The only uncertainty 

is how the rate of change will vary from

place to place. 

Conclusion

Rapid change is the order of the day in

crime mapping. It’s tempting to hold out

and ride the next wave of innovation,

skipping the present phase that is doomed

to obsolescence as soon as the shrinkwrap comes off the software package or

hardware box. This seems to have two

advantages in the short term: minimizing

costs and reducing the need for training.

The problem with this approach is that the

time is never right because another wave

of innovation is always on its way.

Policing is undergoing a paradigm shift

resembling the kind of change that Kuhn

(1962) described three decades ago in 

his book The Structure of Scientific

Revolutions. A paradigm shift is the idea

that, from time to time, various realms of

human endeavor experience dramatic—

almost revolutionary—changes. Kuhn

applied the term to changes in science,

such as the transition in biology from

thinking in terms of whole organisms to a

molecular or genetic perspective. Although

it is pretentious to put changes in crime

mapping on the same level with major

changes in natural science, it is realistic 

to use the notion of a paradigm shift to

understand the nature of changes in the

technology of policing.

It is easy to underestimate or overestimate

the rate of change and the long-term

impact of technological changes in 

167

Mapping Crime: Principle and Practice

Chapter 6
Crime Mapping Futures

policing—including crime mapping. While

current and future advances promise to

lend substantial support to law enforcement, we should remember that technologies such as crime mapping are only tools

and, like other tools, their benefits to society depend on the human agents who

wield them.

Summary

Chapter 6 has explained:

■ What types of changes may be 

expected in crime mapping in the 

next decade.

■ What geographic profiling is and how

it can be useful.

■ High-resolution GIS and how it can 

be applied.

■ How complex statistical methods can

be used in spatial forecasting.

■ Why digital aerial photography is 

finding applications in crime mapping.

■ How various kinds of data visualization can be productively integrated.

■ How GIS and GPS can work together.

■ How the World Wide Web may both

increase and limit data access.

■ Why we can expect continuing debate

on public access to crime data and the

results of crime analysis.

■ What to expect in terms of applications

of multimedia and integration

technologies.

Notes

1. This interpretation and the accompanying map were provided by Det. Insp. D.

Kim Rossmo of the Geographic Profiling

Section, Vancouver Police Department,

Vancouver, British Columbia, Canada.

2. According to a reviewer with profiling

experience, however, profiling is an

extremely specialized and expensive

process demanding a skill level and financial commitment that few agencies can

realistically afford, at least not with the 

currently available technology.

3. For more information on yellow pages

and phone books on CD-ROM, see

http://www.phonedisc.com/.

4. I am indebted to Dr. S.K. Lodha

(University of California, Santa Cruz) and

Dr. Armind Verma (Indiana University) for

the maps and accompanying interpretation. The maps shown are from Lodha

and Verma, 1999. Available online at

http://wcr.sonoma.edu/v1n2/lodha.html.

5. See chapter 2 for additional explanation.

6. A square mile is 1,760 yards x 3 =

5,280 feet2

or 27,878,400 square feet.

7. This pilot project was known as OPRA,

for Orthophotographic Representation and

Analysis.

168 Chapter 6
169

Mapping Crime: Principle and Practice

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Appendix: 

Internet Resources 

for Crime Mapping

U.S. Department of Justice

Crime Mapping Research Center (CMRC) http://www.ojp.usdoj.gov/cmrc

Web site

Office of Justice Programs

National Institute of Justice

Provides links to police departments, 

software vendors, and government 

agencies and is a good starting point for 

an exploration of crime mapping.

Crimemap listserv listproc@aspensys.com

Connects interested subscribers to one In the body of the message, type: 

another and to CMRC and broadcasts SUBSCRIBE CRIMEMAP Your Name

messages to subscribers, such as 

announcements of upcoming conferences 

and solicitations. Participants can share 

knowledge and questions through this 

e-mail address.

Spatial Crime Analysis Section, http://www.usdoj.gov/criminal/gis/

Criminal Division, Web site scashome.htm

Crime Mapping and Analysis Program, http://www.nlectc.org/nlectcrm/

National Law Enforcement and cmap.html

Corrections Technology Center

Web Sites Displaying Crime Maps

Berkeley, CA, Police Department http://inberkeley3.ci.berkeley.ca.us/

annual_rpts/annual.html

Cambridge, MA, Police Department http://www.ci.cambridge.ma.us/~CPD
Appendix: Internet Resources for Crime Mapping

Charlotte-Mecklenburg, NC, http://www.ci.charlotte.nc.us/cipolice/

Police Department spab/gis/cmpd_gis.htm

Clearwater-Pinellas County, FL, http://www.co.pinellas.fl.us/bcc/juscoord/

Police Department enforcer.htm

Detroit (Tri-County), MI, Police Department http://www.cus.wayne.edu/

U_safety/pdfs/handbook.pdf 

Evansville Courier & Press, Evansville, IN http://www.evansville.net/courier/crime

Portland, OR, Police Department http://www.worldstar.com/

~carltown/crmemap.htm

Sacramento, CA, Police Department http://www.sacpd.org/templates/

f-nstart.html

Salinas, CA, Police Department http://www.salinaspd.com/maps.html

San Antonio, TX, Police Department http://www.ci.sat.tx.us/sapd/maps.htm

San Diego, CA, Police Department http://www.sannet.gov/police/

crime-facts/crimanal.shtml

Tempe, AZ, Police Department http://www.tempe.gov/cau

Note: This current list can be found at http://www.ojp.usdoj.gov/cmrc/weblinks/

welcome.html.

GIS and Analysis Software and Other Resources

Environmental Systems Research Institute http://www.esri.com

(ESRI): Arc/Info®, ArcView®

MapInfo® http://www.mapinfo.com

Idrisi http://www.clarklabs.org

Illinois Criminal Justice Information http://www.icjia.state.il.us

Authority and Spatial and Temporal 

Analysis of Crime (STAC) User’s Forum

Guidebook for Measuring Crime in Public http://huduser.org/publications/

Housing with Geographic Information pubasst/gis/html

Systems, $5. 

182
183

Mapping Crime: Principle and Practice

GIS Tutorial

GISTutorial Workbook http://www.heinz.cmu.edu/gistutorial

Hot Spot Identification Methods (see Jefferis, 1999)

Geographic Analysis Machine (GAM) http://www.ccg.leeds.ac.uk/

smart/gam/gamin.html

Spatial and Space-Time Scan Statistic http://www.dcpc.nci.nih.gov/bb/

(SaTScan) software.html

Spatial Pattern Analysis Machine (SPAM) http://athene.csu.edu.au/~jratclif/

ware/spam1.htm

Spatial and Temporal Analysis of Crime http://www.icjia.org/

(STAC) (PDF format)

Vertical MapperTM http://www.northwoodgeo.com

Spatial Analyst http://www.esri.com/software/

arcview/extensions/spatext.html

Idrisi http://www.clarklabs.org

CrimeStat http://www.icpsr.umich.edu/NACJD/

crimestat.html

SpaceStat http://www.bruton.utdallas.edu/

anselin/anselin.htm

Note: This current list can be found at http://www.ojp.usdoj.gov/cmrc/weblinks/

welcome.html

Research Organization

Police Executive Research Forum: http://www.policeforum.org/

Crime Mapping Case Studies, Volumes I 

and II, and other issues relating to law 

enforcement
Appendix: Internet Resources for Crime Mapping

Computer Mapping Laboratory

Police Foundation: Publishes Crime http://www.policefoundation.org 

Mapping News, a quarterly bulletin on 

crime mapping, which emphasizes 

successful implementation of computer 

mapping in law enforcement

Free Sources of Census Data

CIESIN http://www.ciesin.org

U.S. Census Bureau http://www.census.gov

Proprietary Source of Census Data 

GeoLytics: Sells CensusCD+MapsTM directly http://www.censuscd.com/cdmaps/

for $249.95 for a single user license; censuscd_maps.htm

$750 for LAN/CD-Tower license.

Global Positioning Systems (GPS)

Tutorial http://www.trimble.com

Overview http://www.utexas.edu/depts/grg/

gcraft/notes/gps/gps.html

Global Positioning Systems World Magazine http://www.gpsworld.com

Virtual Reality (VR) Viewers

Sample VR tour http://www.nga.gov/exhibitions/

webtours.htm

Quick-time viewer http://www.apple.com

Live-picture viewer http://www.livepicture.com

Examples of VR applications in a http://www.nashville.net/~police/

police department VRMovies/index.htm

184
185

Mapping Crime: Principle and Practice

Other Sources

Coordinate Systems http://www.utexas.edu/depts/grg/

gcraft/notes/coordsys/coordsys.html

Hunter College, New York, NY http://everest.hunter.cuny.edu/capse/

projects/nij/crime.html

International Association of Crime Analysts http://www.iaca.net/

Metadata Standards and Information http://fgdc.gov/standards/standards.html

http://www.blm.gov/gis/nsdi.html

http://www.blm.gov/gis/meta/

minimum.html

The Omega Group (CrimeView® geographic http://www.theomegagroup.com/

analysis product) Map Gallery crimevw.htm

University Consortium for Geographic http://www.ucgis.org

Information Science

To contact the author, e-mail Keith Harries at harries@research.umbc.edu.
187

Mapping Crime: Principle and Practice

Index

abstraction 10, 13, 22, 30, 32, 38-40,

49, 50, 61-63, 160

activity space 29, 136

aggregate 40, 74, 109

aggregating data 105

area 3, 4, 8, 10-14, 16, 18-20, 22-26,

29, 30, 33, 36, 40, 42, 43, 45-51, 53,

54, 56, 57, 59, 60, 62-64, 68, 71-73,

75, 77-79, 81-83, 89, 92, 96, 97, 102,

105, 107-109, 112, 113, 115-121, 124,

126-131, 133, 136, 139, 140, 142, 146,

148, 151-155, 159, 164, 165, 169, 179

ASCII file 121

autodialer 139, 171

balance 31, 59, 63

base map 2, 25, 89, 91, 99, 103, 104

batch matching 99

box plot 56, 57

breakpoints in crime data 50, 51

buffering 90, 118, 119, 125, 130

calls for service 42, 45, 68, 71, 72, 86,

94, 102, 103, 114, 119, 123, 129, 134,

137, 146, 147, 156, 159

cartogram 30, 32

cartographic school 4

cartography 3, 4, 6, 8, 13, 14, 17, 30,

31, 39, 52, 57, 64, 84, 130, 171, 175,

177-179

census 5, 8, 15, 20, 24, 40, 43, 47, 72,

74, 77, 78, 92, 96-98, 102, 108, 112,

120-123, 126, 129, 130, 146-148, 160,

162, 166, 171, 176, 177, 180, 184

centroid 102, 108, 109

choropleth map 24, 40, 42, 45-48, 50,

51, 55, 57, 64, 65, 92, 115, 124, 146,

156

chroma 60, 61

classes of data 50

classifying map information 124

cluster analysis 115, 117

CMRC, see Crime Mapping Research

Center

color 1, 3, 7, 8, 9, 17, 31, 32, 41, 47,

50, 54, 57, 60-63, 69, 87, 88, 100, 114,

116, 124, 152, 158-160

community organizations 88, 89

community oriented policing iii, 64, 80,

82, 90, 147

community policing 8, 77, 82, 120, 134,

144, 146, 160, 162, 163, 171
Index

computational model 39

ComStat 78-80, 142

continuous distribution 20

coordinate system 14-17, 31, 59, 65, 

82, 185

COP, see community oriented policing

corrections vii, 64, 67, 84, 90, 126, 136,

139, 141, 148, 164, 165

costs 10, 31, 92, 94, 128, 132, 163, 167

courtroom presentation 144

courts vii, 64, 84, 90, 126, 136, 139,

144, 148, 167

Crime Mapping Research Center iii, iv, v,

3, 40, 115, 146, 174, 175, 180, 181

crime prevention 5, 8, 29, 75, 126, 128,

134, 136-139, 148, 160, 164, 170-173,

175-177, 179, 180

criminal geographic targeting 152

criminal intelligence 126, 136, 137, 

148, 159

criminal spatial behavior 28, 29, 178

cue 29, 39, 122

curtilage, see street curtilage

custom 30, 52, 61, 64, 94, 116, 123

dasymetric mapping 57, 64

data exploration 112

data integration 110, 147

data mining 90, 123, 125, 167, 177

data sharing 128, 133, 134, 166

data visualization 6, 149, 168

data warehousing 90, 123, 125, 177

demographic change 67, 71, 76

density 4, 20, 23, 25, 28, 42, 45, 46, 48,

57, 64, 73, 74, 81, 105-108, 113, 128,

129, 159

density analysis 105

derivative measure 53, 90, 109, 125

desktop mapping 2, 3, 6, 42, 50, 51

DGPS, see differential positioning GPS

differential positioning GPS 164

digital aerial photography 152, 168

digital orthophoto quadrangle 160

direction 15, 17, 18, 32, 33, 98, 100,

112, 129, 141, 154, 162

discrete distribution 20, 24

displacement 67, 71, 75, 76, 105, 130,

139, 169, 180

distance 11, 15, 17-19, 21, 23, 27, 28,

30, 38, 54, 108, 109, 112, 117, 141,

152

distance decay 27, 28

188
189

Mapping Crime: Principle and Practice

DOQ, see digital orthophoto quadrangle

dot map 40

EDA, see exploratory data analysis

equal area 51

equal count 51, 54

equal range 51, 54

ESDA, see exploratory spatial data 

analysis

exploratory data analysis 123

exploratory spatial data analysis

36, 53, 123

Federal Geographic Data Committee 110,

111, 185

Federal Information Processing Standard

code 121

FGDC, see Federal Geographic Data

Committee

filtering 38, 90, 100, 101, 103, 104,

107, 125, 160

flow map 48, 49

focus of attention 9, 59, 60, 63

forecasting 149, 151, 152, 155, 156, 168

function 64, 69, 76, 79, 108-110, 113,

117, 120, 123, 127, 130, 152

geocoding 90, 92, 97-100, 125, 127,

129, 142, 164, 169

geographic information system v, 4, 6,

10, 12, 17, 33, 38, 49, 57, 60, 61, 83,

84, 87, 90-92, 94, 95, 97, 98, 100, 105,

107-112, 114, 119-122, 124-127, 129,

130, 136, 137, 139, 140, 142, 149, 151,

152, 155, 159, 160, 164, 165, 167, 168,

170-176, 178-183, 185

geographic profiling 137, 149, 152,

154, 168

geographic school 4

geoprofile 153, 154

GIS, see geographic information system

GIS software 17, 61, 94, 100, 107,

109, 121

global-local precedence 22

global positioning system 64, 78, 94,

123, 131, 149, 151, 152, 164-166,

168, 179, 184

GPS, see global positioning system

grid cell analysis 115, 116

halfway house location 142

high-resolution GIS 149, 152, 155, 168

histogram 8, 54, 56, 58, 152, 159

hit rate 99, 100

hot spot 11, 19, 56, 74, 75, 94, 112-

116, 118, 125, 126, 138, 139, 169, 183

hot spot mapping 71, 74, 115, 118
Index

hue 60, 61

hypothesis 7, 8, 36, 37, 123

hypothetic-deductive method 37

hypothetic-deductive process 8

ICAM, see Information Collection for

Automated Mapping

immigrant group 77

incident 4, 11, 20, 23-26, 28, 30, 36, 40,

42, 62, 67, 69, 71-73, 75, 84, 87, 92,

94, 100, 102, 103, 105, 107, 108, 113-

117, 120, 134, 137, 139, 144, 155, 163,

164, 166, 167, 169

inclusion 31, 59, 63, 108

Information Collection for Automated

Mapping 69, 128, 178

integration 110, 126, 131, 149, 151,

152, 162, 164, 167, 168

intermediate scale 26

internal organization 59, 60, 63

interval measurement 8, 12, 23, 24, 32,

51, 52, 54, 55, 63, 116, 124, 159

investigator 18, 36, 37, 64, 67, 70, 

90, 136

isoline map 24, 64, 159

Jenks’ Optimization 51

jeopardy surface 152

journey to crime 28

latitude 14-17, 32, 33, 40, 59, 98, 152

layering 92, 110

legibility 10, 20, 32, 61-63

line data 19, 20, 130

linear map 25

linear symbol 25, 48, 49

linkage blindness 133

location 8, 11, 14-18, 20, 24, 28, 33, 36,

40, 42, 43, 45, 62, 65, 69, 71, 74, 77,

80, 83, 84, 86, 87, 96, 98, 99, 103-105,

112, 115, 116, 118-121, 129, 130, 132,

133, 136-143, 152, 162-166, 170, 174,

180

longitude 4, 14-17, 32, 33, 40, 59, 98,

152, 179

macro scale 26

map composition 59

map design 6, 8, 18, 31, 32, 45, 57, 

61-63, 67, 89, 171, 177

map element 8, 17, 18, 60, 62, 124, 130

map projection 13, 14, 16, 31, 123

mapping space 102

mapping time 101, 102, 180

match score 100

meridian, see longitude

metadata 110, 111, 185

190
191

Mapping Crime: Principle and Practice

micro scale 22, 26, 29

mimetics 63, 65

minorities 77, 78

modus operandi 37, 103, 104, 139, 142

MO, see modus operandi

multimedia 149, 167, 168

NAD, see North American Datum

National Spatial Data Infrastructure

110, 185

natural break 54

nominal measurement 23

North American Datum 16

NSDI, see National Spatial Data

Infrastructure

offender access to services 144

operator 109, 132

ordinal measurement 23

orthophoto 10, 97, 131, 132, 151, 

160-164, 168

overlap 1, 26, 38, 45, 80, 84, 94, 108,

115, 126, 152, 157

parallel 14-16, 32, 59, 159, 165

parolee location 142

patrol area 11, 20, 23, 24, 40, 67, 72,

96, 102, 108

patrol officer 64, 67, 69, 72, 90, 94, 119,

153, 164

pattern 1, 3, 4, 18, 19, 25, 26, 28, 29,

31, 32, 36, 37, 39, 46, 56, 60, 68, 70,

74, 76, 80, 89, 99, 104, 115, 116, 124,

128, 130, 133, 134, 136-139, 142, 144,

154-156, 169-173, 175, 183

pattern recognition theory 39

Pauly Areas 92

perspective symbol landmark 63

pin map v, 1-3, 20, 24, 40, 42, 49, 79,

87, 94, 116, 156-158

place v, 3, 7, 11, 16-20, 24, 25, 28, 31,

33, 38, 40, 42, 46, 54, 60, 67, 71, 74,

75, 77, 96, 112, 123, 133, 145, 157,

164, 167, 169, 170, 172, 176, 178-180

point map, see pin map 

police manager 67, 71, 90

POP, see problem oriented policing

presentation vii, 20, 22, 25, 31, 35, 38,

42, 48, 50, 51, 54, 56, 62, 80, 87-89,

115, 142, 144, 160, 163

principle of least effort 27

prison location 140

privacy issues 128, 134

probation 82, 104, 105, 139-142,

162, 165

probationer location 139, 140, 142, 

162, 165
Index

problem oriented policing 64, 80, 82, 90

public access 128, 135, 166, 168

public information 126, 136, 144, 146,

148, 160, 166

qualitative map 23

RAM, see repeat address mapping

raster 90, 95-97, 121, 125, 131, 132,

159, 161, 162, 172

ratio 21, 23, 40, 50, 109

RCAGIS, see Regional Crime Analysis GIS

Regional Crime Analysis GIS 126

repeat address mapping 6, 74, 163

representative fraction 21, 22, 62, 160

resource allocation 67, 72, 73, 87, 92,

126, 136, 146, 148

RF, see representative fraction

Rigel 152

risk and protective focused prevention

83, 174

routine activities 28, 29, 171

scale 1, 10, 15, 17, 18, 21-24, 26, 30,

31, 33, 38, 45, 46, 48-50, 56, 59, 62,

63, 84, 87, 88, 96, 97, 109-111, 113,

119, 123, 124, 126, 136, 144, 155, 160

selecting 12, 52, 83, 100, 101, 119

sentence mapping 144

situational crime prevention 29, 171

social ecologist 4

social ecology school 4

space 1, 4, 11-15, 19, 28, 29, 31, 46,

56, 59, 60, 79, 96, 104, 112, 113, 115,

138, 157, 161, 163, 165, 169, 179, 183

spatial autocorrelation 115, 118, 178

spatial experience 38

stage model 39

standard deviation 8, 9, 51, 54, 58, 154

State Plane Coordinate System 16

statistical map 24, 42, 53

statistical symbol 24, 42, 45, 108

street curtilage 115

surface map 13, 25, 40, 48, 64, 116

survey 38, 46, 78, 86, 94, 113, 115,

128, 129, 146, 175, 180

SYMAP 92

SYMVU 21, 92

synthesis 38, 50, 134

technology imbalance 127, 128

template 3, 29, 182

192
193

Mapping Crime: Principle and Practice

thematic map 23, 24, 32, 40, 42, 45, 

48-50, 57, 59, 63

TIGER, see Topologically Integrated

Geographic Encoding and Referencing

time vii, 1, 6, 7, 11-13, 18, 30, 31, 33,

37, 39, 42, 45, 49, 52, 56, 57, 59, 62,

67, 69, 71, 75, 76, 79, 80, 96, 101-104,

111-115, 129-131, 137-139, 141, 142,

145, 157-159, 164, 166, 167, 178, 179,

183

TIN, see triangulated irregular network

Topologically Integrated Geographic

Encoding and Referencing 97, 98, 169,

171, 176, 180

triangulated irregular network 96

typological school 4

Universal Transverse Mercator Coordinate

System 16, 17

value 1, 8, 9, 15, 23-25, 33, 34, 45, 47,

48, 52-54, 56-58, 60, 61, 64, 72, 77,

89, 95, 96, 102, 105, 108, 109, 115,

116, 121, 123, 124, 126, 144, 145, 147,

159, 160, 164

vector 90, 95, 96, 97, 125

virtual reality 158, 162, 163, 175, 184

Virtual Reality Modeling Language 158

visual communication 8, 10, 35-38

visual thinking 35-38, 50

VRML, see Virtual Reality Modeling

Language

Web, see World Wide Web

World Wide Web v, 3, 17, 40, 59, 64, 78,

121-123, 128, 135, 136, 144, 146, 151,

163, 166, 168, 181
For more information on the National Institute of Justice, please contact:

National Criminal Justice Reference Service

P.O. Box 6000

Rockville, MD 20849–6000

800–851–3420

E-mail: askncjrs@ncjrs.org

To access the World Wide Web site, go to

http://www.ncjrs.org

If you have any questions, call or e-mail NCJRS.
About the National Institute of Justice

The National Institute of Justice (NIJ), a component of the Office of Justice Programs, is the research agency of 

the U.S. Department of Justice. Created by the Omnibus Crime Control and Safe Streets Act of 1968, as amended,

NIJ is authorized to support research, evaluation, and demonstration programs, development of technology, and 

both national and international information dissemination. Specific mandates of the Act direct NIJ to:

● Sponsor special projects, and research and development programs, that will improve and strengthen the 

criminal justice system and reduce or prevent crime. 

● Conduct national demonstration projects that employ innovative or promising approaches for improving 

criminal justice. 

● Develop new technologies to fight crime and improve criminal justice. 

● Evaluate the effectiveness of criminal justice programs and identify programs that promise to be successful if 

continued or repeated. 

● Recommend actions that can be taken by Federal, State, and local governments as well as by private organizations

to improve criminal justice. 

● Carry out research on criminal behavior. 

● Develop new methods of crime prevention and reduction of crime and delinquency. 

In recent years, NIJ has greatly expanded its initiatives, the result of the Violent Crime Control and Law Enforcement

Act of 1994 (the Crime Act), partnerships with other Federal agencies and private foundations, advances in 

technology, and a new international focus. Some examples of these new initiatives:

● New research and evaluation are exploring key issues in community policing, violence against women, sentencing

reforms, and specialized courts such as drug courts. 

● Dual-use technologies are being developed to support national defense and local law enforcement needs. 

● The causes, treatment, and prevention of violence against women and violence within the family are being 

investigated in cooperation with several agencies of the U.S. Department of Health and Human Services. 

● NIJ’s links with the international community are being strengthened through membership in the United Nations 

network of criminological institutes; participation in developing the U.N. Criminal Justice Information Network;

initiation of UNOJUST (U.N. Online Justice Clearinghouse), which electronically links the institutes to the 

U.N. network; and establishment of an NIJ International Center. 

● The NIJ-administered criminal justice information clearinghouse, the world’s largest, has improved its 

online capability. 

● The Institute’s Drug Use Forecasting (DUF) program has been expanded and enhanced. Renamed ADAM 

(Arrestee Drug Abuse Monitoring), the program will increase the number of drug-testing sites, and its role 

as a “platform” for studying drug-related crime will grow. 

● NIJ’s new Crime Mapping Research Center will provide training in computer mapping technology, collect and

archive geocoded crime data, and develop analytic software. 

● The Institute’s program of intramural research has been expanded and enhanced. 

The Institute Director, who is appointed by the President and confirmed by the Senate, establishes the Institute’s 

objectives, guided by the priorities of the Office of Justice Programs, the Department of Justice, and the needs of 

the criminal justice field. The Institute actively solicits the views of criminal justice professionals and researchers 

in the continuing search for answers that inform public policymaking in crime and justice.
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Table of Contents

NCJ 178919

What's New | Programs | Funding | Publications | Contact NIJ | About NIJ

NIJ-Related Sites | Search | Home
Mapping Crime: Principle and Practice -- Table of Contents

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Table of Contents

Introduction

Acknowledgments

Foreword

Preface

Chapter 1: Context and Concepts

Chapter 2: What Crime Maps Do and How They Do It

Chapter 3: Maps That Speak to the Issues

Chapter 4: Mapping Crime and Geographic Information Systems

Chapter 5: Synthesis and Applications

Chapter 6: Crime Mapping Futures

References

Appendix

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
Mapping Crime: Principle and Practice -- Front Matter

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Introduction

U.S. Department of Justice

Office of Justice Programs

810 Seventh Street N.W.

Washington, DC 20531

Janet Reno

Attorney General

Daniel Marcus

Acting Associate Attorney General

Laurie Robinson

Assistant Attorney General

Noel Brennan

Deputy Assistant Attorney General

Jeremy Travis

Director, National Institute of Justice

Office of Justice Programs

World Wide Web Site

http://www.ojp.usdoj.gov

National Institute of Justice

World Wide Web Site

http://www.ojp.usdoj.gov/nij

Mapping Crime:

Principle and Practice

Keith Harries, Ph.D.

December 1999

NCJ 178919

National Institute of Justice

Jeremy Travis

Director

Nancy La Vigne

Program Monitor

This project was supported by Grant No. 98-LB-VX-0009 awarded by the

National Institute of Justice, Office of Justice Programs, U.S. Department of

Justice. Points of view in this document are those of the author and do not

necessarily represent the official position or policies of the U.S. Department of

Justice.

Cover Credits

Clockwise, starting with upper left corner:

Map by Lodlha and Verma, 1999

Map by Jeff Stith and the Wilson, North Carolina, Police

Department

Map by Wilpen Gorr, Heinz School of Public Policy and
Mapping Crime: Principle and Practice -- Front Matter

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Management, Carnegie Mellon University, Pittsburgh,

Pennsylvania

Map by Susan Wernicke, Overland Park, Kansas, Police

Department

Map by ASDI Technologies, Colorado Springs, Colorado

Map by Jeff Stith and the Wilson, North Carolina, Police

Department

The National Institute of Justice is a component of the Office of Justice

Programs, which also includes the Bureau of Justice Assistance, the

Bureau of Justice Statistics, the Office of Juvenile Justice and Delinquency

Prevention, and the Office for Victims of Crime.

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
Mapping Crime: Principle and Practice -- Acknowledgments

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Acknowledgments

Without the generous cooperation of many people in various settings, including

police departments and universities, the variety of examples and particularly

illustrations presented in this guide would not have been possible. Some

individuals who should have been acknowledged below may have been

inadvertently omitted, and I apologize if that is the case. Among those who

must be singled out for special recognition are the following (in alphabetical

order):

Al Ball, Office of Community Oriented Policing Services (COPS) Regional

Institute, Cincinnati, Ohio; Rachel Boba, Tempe Police Department, Tempe,

Arizona; Chris Bruce, Cambridge Police Department, Cambridge,

Massachusetts; Jim Bueermann, Redlands Police Department, Redlands,

California; Philip Canter, Baltimore County Police Department, Towson,

Maryland; Peter Dana, University of Texas, Austin, Texas; Wilpen Gorr, Heinz

School, Carnegie Mellon University, Pittsburgh, Pennsylvania; Elizabeth Groff,

Crime Mapping Research Center, National Institute of Justice, Washington,

D.C.; Hal Holtzman, U.S. Department of Housing and Urban Development,

Washington, D.C.; James LeBeau, Southern Illinois University, Carbondale,

Illinois; Suresh K. Lodha, University of California, Santa Cruz, California; Mark

Mattson, Temple University, Philadelphia, Pennsylvania; Tom McEwen, Institute

for Law and Justice, Alexandria, Virginia; Phillip G. McGuire, New York City

Police Department, New York, New York; Sara McLafferty, Hunter College,

New York, New York; Robert Moland, St. Petersburg Police Department, St.

Petersburg, Florida; Tracy Molfino, Salinas Police Department, Salinas,

California; Lew Nelson, Environmental Systems Research Institute, Inc.,

Redlands, California; Mike Neumann, Cincinnati Police Department, Cincinnati,

Ohio; Andreas Olligschlaeger, Carnegie Mellon University, Pittsburgh,

Pennsylvania; George Rengert, Temple University, Philadelphia, Pennsylvania;

D. Kim Rossmo, Vancouver Police Department, Vancouver, British Columbia,

Canada; Mark Stallo, Dallas Police Department, Dallas, Texas; Gerry Tallman,

Overland Park Police Department, Overland Park, Kansas; Deb Thomas,

University of South Carolina, Columbia, South Carolina; Arvind Verma, Indiana

University, Bloomington, Indiana; Julie Wartell, Institute for Law and Justice,

Alexandria, Virginia; John Werner, Mesa Police Department, Mesa, Arizona;

Susan Wernicke, Overland Park Police Department, Overland Park, Kansas;

Doug Williamson, Center for Applied Studies of the Environment (CAPSE), City

University of New York, New York, New York.

I am particularly grateful to Nancy La Vigne, director of the National Institute of

Justice (NIJ) Crime Mapping Research Center, who facilitated this project.

Several reviewers, anonymous and otherwise, provided invaluable insight that

has been incorporated. I am also grateful to my colleague Tom Rabenhorst,

former cartographic editor of Annals of the Association of American

Geographers, who edited the maps.

Ultimately, all these efforts to spread the blame are in vain, and the author

accepts full responsibility for errors, omissions, and misinterpretations.

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
Mapping Crime: Principle and Practice -- Acknowledgments

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Mapping Crime: Principle and Practice -- Foreword

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Foreword

In 1997, when the National Institute of Justice (NIJ) was planning to create its

Crime Mapping Research Center (CMRC), we convened a 2-day strategic

planning meeting to seek advice on the Center's goals, direction, and mission.

Before the meeting, we had assumed that many agencies were already using

mapping and that NIJ's goal would be to encourage the field to move beyond

descriptive mapping (e.g., pin maps) toward analytic mapping. The meeting

helped us recognize that another goal must be to assist the large number of

agencies that are not using mapping.

Keith Harries, who received one of the first grants from CMRC, has prepared

this comprehensive guide for agencies that are in the early stages of using

geographic information systems (GIS). His words are directed to law

enforcement professionals who have a little knowledge about GIS and want to

learn more about its benefits and limitations.

He has collected more than 110 maps to illustrate how GIS is used. These

pictures express the truth of the phrase "one picture is worth a thousand

words."

Dr. Harries' guide is not designed to stand alone. Law enforcement agencies

will need other curriculum materials as well-especially software manuals—but it

will be a starting place. Additional materials and links to other sources of

information can be found at CMRC's World Wide Web site

(http://www.ojp.usdoj.gov/nij/maps/). As a clearinghouse of information about

crime mapping, CMRC also sponsors a listserv (listproc@aspensys.com), which

has more than 640 subscribers, and an annual conference, which draws more

than 700 attendees.

Today about 13 percent of law enforcement agencies are using GIS regularly to

analyze their crime problems, and we are certain to see this number increase

significantly as more and more agencies begin using computerized crime

mapping to identify and solve their crime problems. We hope this guide will help

them get started. For agencies that are already using crime mapping

technology, we hope this guide will spark ideas about new ways to use it.

Jeremy Travis

Director

National Institute of Justice

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
Mapping Crime: Principle and Practice -- Preface

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Preface

This guide introduces the science of crime mapping to police officers, crime

analysts, and other people interested in visualizing crime data through the

medium of maps. Presumably most readers will be working in law enforcement

agencies, broadly interpreted to include courts, corrections, the military police,

and Federal agencies such as the FBI, U.S. Bureau of Alcohol, Tobacco and

Firearms, National Park Service, U.S. Customs Service, and U.S. Secret

Service, as well as police departments. The material is designed primarily for

those who know little or nothing about mapping crime and who are motivated to

learn more.

This is not a guide to software. Nowhere is there more than a word or two on

how to do anything technical involving a computer. A purely technical guide

would quickly be out of date, and a guide that served one set of software

devotees would not serve others. Technical guidance is best sought from the

manuals and interest groups specific to each software package.

What will be found here is a broad approach addressing the kinds of questions

crime mapping can answer and how, in general terms, it can answer them.

Caveats are given from time to time, notably the caution against uncritically

accepting all the default settings that crime mapping software so conveniently

provides.

Most readers will not read this guide from cover to cover. Some will concentrate

on application-oriented material. Others will have an interest in the history of

crime mapping, realizing that where we have been can help us figure out where

we are going.

The presentation employed in this guide leans heavily on examples. Indeed,

the guide is made up of examples with the words draped around them. Crime

analysts and researchers from across the United States and from Canada and

the United Kingdom have contributed. Without their help, this guide would be

an empty shell. I am extremely grateful to all who donated their work so

graciously, and a partial listing of these kind souls is found in the

acknowledgments.

Keith Harries

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
Mapping Crime: Principle and Practice -- Chapter 1: Context and Concepts-Contents

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Chapter 1: Context and Concepts

Contents

From pins to computers

Ancient history: Cartography and crime mapping

Mapping as a special case of data visualization

Mapping as art and science

Maps as abstractions of reality: Benefits and costs

Crime incidents: Measuring time and space

Map projection

Coordinate systems

Map elements: The usual bits and pieces

Types of map information

Scale

Maps of crime: Thematic maps

Data, maps, and patterns

Other theoretical perspectives

A note on cartograms

Reminder: Information is inevitably lost in the process of abstraction

A note on the maps in this guide

Summary

Notes

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
Mapping Crime: Principle and Practice -- Chapter 2: What Crime Maps Do and How They Do It-Contents

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Chapter 2: What Crime Maps Do and

How They Do It

Contents

What crime maps do

How crime maps do what they do

Choosing a crime map

Examples of thematic maps

Classifying map information

Maps and statistics: Exploratory spatial data analysis

Map design

Design, abstraction, and legibility

Summary

Notes

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
Mapping Crime: Principle and Practice -- Chapter 3: Maps That Speak to the Issues-Contents

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Chapter 3: Maps That Speak to the

Issues

This chapter discusses how map designs can address specific issues and

audiences. The underlying assumption that "one map fits all" is inadequate

because each audience has its own perspective on crime and how it can be

prevented or controlled. Community leaders may have the latest notorious

incident on their minds. Policymakers may be concerned about how to trim $1

million-$2 million from their budgets while making the community safer.

Members of the court and corrections communities may be concerned with

overloaded systems, overcrowding, and the ramifications of releasing offenders

early. Investigators may need tools to help them organize place-related facts

and processes. Police managers often worry about accountability, resource

allocation, displacement problems, and the implications of demographic change.

On the front lines where patrol and community officers operate, community

information is a core resource rarely available in sufficient quantity or quality.

Contents

Patrol officers

Investigators

Police managers

Maps in support of community oriented policing and problem oriented

policing

Maps and community policing: The city of Redlands, California, approach

Courts and corrections

Policymakers: The medium and the message

Community organizations

Conclusion

Summary

Notes

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
Mapping Crime: Principle and Practice -- Chapter 4: Mapping Crime and Geographic Information Systems-Contents

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Chapter 4: Mapping Crime and

Geographic Information Systems

Contents

The GIS revolution

The GIS perspective

Spatially enabling the data: What is geocoding?

Data selecting, filtering, and mapping according to useful criteria

Selecting and displaying specific information

Using GIS to measure from maps: Aggregating data

Derivative measures: How to create new indicators

GIS as a tool for data integration and exploration

Hot spots

Buffering: Meaning and applications

Data, data, everywhere: What's an analyst to do?

Cautions

Summary

Notes

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
Mapping Crime: Principle and Practice -- Chapter 5: Synthesis and Applications-Contents

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Chapter 5: Synthesis and Applications

This chapter brings together concepts discussed previously and gives an

overview of crime mapping applications in selected areas of criminal justice.

Contents

Synthesis 2000

Mapping applications for the millennium

Crime analysis and the census

Conclusion

Summary

Notes

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
Mapping Crime: Principle and Practice -- Chapter 6: Crime Mapping Futures-Contents

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Chapter 6: Crime Mapping Futures

Applications in crime mapping are becoming increasingly sophisticated and

integrated. The hallmark of the first decade or so of the modern era of crime

mapping was the use of geographic information systems (GIS). Perhaps the

next decade will see the integration of previously separate technologies such as

global positioning systems (GPS), orthophotography, digital photography, digital

videography, and a wide range of local databases with relevance to policing—

and the World Wide Web. Another realm of potential progress lies in

forecasting. A remarkable indication of the level of interest in crime mapping

and related technologies was contained in President Clinton's State of the

Union Address on January 19, 1999, in which he said:

Tonight, I propose a 21st century Crime Bill to deploy the latest

technologies and tactics . . . [to] put up to 50,000 more police on

the street in the areas hardest hit by crime, and then to equip

them with new tools from crime—mapping computers to digital

mug shots. [Emphasis added.]

While it is not possible to explain or even identify all the innovative crime

mapping applications in the field or under development, the following are

outlined below to provide a sense of the kinds of methods and technologies that

are likely to find increasing acceptance in the years ahead: geographic profiling,

which has already found wide recognition and is representative of a method that

creatively combines various tools of spatial analysis; high-resolution GIS;

statistical methods and forecasting; digital aerial photography; and the

integration of GIS and GPS.

Contents

Geographic profiling

High-resolution GIS

Forecasting: Complex statistical methods and crime mapping

Digital aerial photography in policing

The integration of GIS and GPS

Conclusion

Summary

Notes

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Mapping Crime: Principle and Practice, by Keith Harries, Ph.D., December 1999
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Mapping Crime: Principle and Practice -- Appendix: Internet Resources for Crime Mapping

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Appendix: Internet Resources for Crime

Mapping

Contents

U.S. Department of Justice

Web Sites Displaying Crime Maps

GIS and Analysis Software and Other Resources

GIS Tutorial

Hot Spot Identification Methods

Research Organization

Computer Mapping Laboratory

Free Sources of Census Data

Proprietary Source of Census Data

Global Positioning Systems (GPS)

Virtual Reality (VR) Viewers

Other Sources

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