Geocoding in Law Enforcement 


Final Report 
Geocoding in Law Enforcement 


Final Report 

Prepared by: 

The Crime Mapping Laboratory 

Police Foundation 

August 2000 

Report to the Office of Community Oriented Policing Services 

Cooperative Agreement #97-CK-WXK-004 

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Table of Contents 


Introduction............................................................................................................................4


The Geocoding Process ..........................................................................................................5 


Step One: Prepare the geographic and tabular files for geocoding ................... 5


Step Two: Specify geocoding parameters...........................................................10


Step Three: Geocode ...............................................................................................11 


Step Four: Review results .....................................................................................14


Step Five: If necessary, respecify parameters and geocode again .................16


Conclusion .............................................................................................................................17


3 

Introduction 


Geocoding is the 

process of 

bringing tabular 

and geographic 

data together... 

...geographic 

data used for 

geocoding are 

called “reference data”... 

Geocoding is the process of bringing tabular and geographic data together based 

on a common geographic unit of analysis. A geographic unit of analysis refers to a 

spatial characteristic within the data that is necessary to locate it on a map such as 

address, zip code, beat, grid, etc. Tabular data are contained in a table and are a list of 

records that, along with information about the record, contain addresses or some other 

type of geographic variable. Examples of law enforcement tabular data are calls for 

service, crime, accidents, citations, sex offenders, and arrests. Along with information 

about the type of call or crime, date, time, etc., these data contain the location of the 

incident (address, grid, and/or beat), which will allow it to be geocoded. Geographic 

data are data that can be displayed on a map such as streets, census tracts, parcels, 

buildings, etc. Examples of geographic data specific to law enforcement are police 

districts, beats, or grid boundaries. 

The purpose of geocoding is to assign tabular data to a location on the earth’s 

surface to visualize the spatial characteristics of the data. It is analogous to placing a 

pin on a map in the appropriate location. Unlike the paper map, when geocoding in a 

geographic information system, data associated with the pin, or data point, are 

available. In order to geocode either electronically or manually, there must be a 

common geographic unit of analysis. In law enforcement, address is primarily used as 

the geographic unit of analysis to which tabular data are geocoded. However, other 

types of geographic units are also used such as parcels, zip codes, census tracts, census 

blocks, or beats. In the case of geocoding, geographic data used for geocoding are 

called “reference data” since the geographic data are used to reference the tabular data. 

The following report is a discussion of the geocoding process, regardless of the 

Geographic Information Systems (GIS) software used, and some common problems 

faced when geocoding law enforcement data. 

4 

The Geocoding Process 


In general, there are five basic steps in the geocoding process. They are: 

1. Prepare the geographic and tabular files for geocoding. 

2. Specify the geocoding parameters. 

3. Geocode. 

4. Review results. 

5. If necessary, respecify parameters and geocode again. 

Step One: Prepare the geographic and tabular files for geocoding 

The first step is preparing the tabular and geographic files, which is the most 

important and can be the most time consuming of the five steps. 

Tabular data. Tabular data used in law enforcement primarily consist of calls 

for service, crime, arrests, and accident data. Other types of tabular law enforcement 

data can include field information, sex registrant information, intelligence information, 

etc. In the past, much of this information was not captured electronically. However, 

currently, many departments either already have in place or plan to acquire an 

automated computer aided dispatch (CAD) system and a record management system 

(RMS) which have the capacity to store digital information as well as standardized 

tables of addresses and location names. The most important aspects of these systems 

as they relate to geocoding are that they reduce the need for manual data entry and 

provide clear and consistent rules in order to ensure that data are reliable and valid. 

Because individuals are the data entry mechanism, there is still the possibility of 

human error and inconsistencies, which is why training should coincide with the 

technology. 

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Street files are 

often called 

centerline files 

in that they 

depict the 

center of the 

streets by line 

segments. 

Geographic data. A variety of geographic data types may be used as a reference 

layer, though street files such as the Census Bureau’s TIGER/Line ® files are the most 

commonly used. Street files are often called centerline files in that they depict the 

center of the streets by line segments. Details of curbs, alleys, cul de sacs, etc. are not 

depicted in centerline files. The following is an example of a street centerline file most 

commonly used. 

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...street files 

are geographic 

databases 

containing 

records that 

describe 

interconnected 

street 

segments. 

In this context, street files are geographic databases containing records that 

describe interconnected street segments. More specifically, each street is broken 

down into sections with address ranges associated with them. These sections usually 

span between cross streets. The following darkened line is an example of a street 

segment. The table below is the accompanying table. 

Street centerline databases generally have fields that describe the physical 

address along each street segment in the layer. Conventionally, addresses are recorded 

as ‘from’ and ‘to’ ranges for both the left and right sides of each street segment. In the 

above example, the centerline street segment of Yale Ave that is thicker than the 

others is represented by the address ranges of 83 to 173 on one side of the street and 

84 to 174 on the other side, as highlighted in the table. 

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In addition to address ranges, street segments can be depicted by several 

variables such as street name, type, prefix, and suffix. Street centerline databases 

vary in how the addresses are described. In the previous example, address is depicted 

with a variable called “street” along with the address ranges. The following are tables 

with highlighted examples of two additional ways in which addresses are found in a 

geographic database. The prefix and suffix fields are used to store information such as 

quadrant. The first table highlights a street segment with the prefix W for West 

Northern Ave. The second table highlights a street segment with the suffix NW for 

Chesterfield Place Northwest. Type refers to the type of roadway, e.g. street, road, lane, 

and drive. The highlighted examples in the following tables show Ave for Northern 

Avenue and Pl for Chesterfield Place. 

Because the Census Bureau’s mission to count and profile the nation’s people 

and institutions does not require very high levels of positional accuracy in its 

geographic products, its TIGER/Line ® files and centerline maps are designed to show 

only the relative position of geographic elements. Some level of correction is generally 

necessary when using these products. 

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A parcel file is a 

polygon layer 

used to keep 

track of lots, 

subdivisions, 

and ownership 

information 

primarily for 

planning and 

tax purposes. 

As previously mentioned, another common layer used as a reference for 

geocoding is the parcel file. A parcel file is a polygon layer used to keep track of lots, 

subdivisions, and ownership information primarily for planning and tax purposes. The 

following is an example of how a parcel map looks in a GIS. Note that it is more specific 

than a centerline map in that alleys, cul de sacs, lot size, and street widths are 

discernable. 

Alley 

Cul de sac 

Individual lot 

Actual street width 

Parcel files provide a good base layer to examine relationships between land 

use, zoning, demographic data, and economic data as all of this information is contained 

in parcel files. Also, parcel reference layers can be very helpful in mapping law 

enforcement information because they can help to indicate the exact location of an 

incident, e.g. corner lot, and provide ownership information which may prove valuable, 

e.g. in the case of rental property. 

While parcel files have the ability to be highly accurate, like street files, this 

accuracy is largely dependent on how often and how well they are maintained. Because 

of the nature of real estate and other planning mechanisms, keeping parcel files 

updated and accurate can be a full-time job for several technicians depending on the 

area. 

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For any crime 

mapping 

application to 

be effective, 

basic reporting 

procedures 

need to be 

uniform and 

consistent. 

Successful geocoding depends not only on the quality of the geographic 

reference layer, but also the tabular data to be mapped. For any crime mapping 

application to be effective, basic reporting procedures need to be uniform and 

consistent. While most high-end geocoding software packages incorporate complicated 

algorithms making them somewhat forgiving, a well established reporting procedure is 

often the best way to ensure a high rate of accuracy. 

Step Two: Specify geocoding parameters 

Step two consists of specifying the parameters of both the reference data and 

the tabular data to determine how the geographic units from each source will be 

matched successfully. 

Selection of which reference layer would be most effectively used for geocoding 

must consider the needs of the individual end user. Considerations of accuracy, cost of 

product, maintenance costs, utility, current reporting procedures, and compatibility 

with other existing reference layers must be dealt with on a case-by-case basis. In the 

case of law enforcement, most information is geocoded to the street reference layer. 

However, sometimes it is necessary to be more specific, in which case a parcel 

reference layer may be used. For example, one might use the street centerline file to 

pin map residential burglaries in an entire city since the exact location of the burglary 

would not be as important as getting a general idea of where the incidents are 

occurring throughout the city. On the other hand, one might use a parcel file to pin map 

residential burglaries in a one or two block area to determine exactly which houses 

were targeted and whether they were along alleys, wooded areas, on the end of the 

block, etc. 

Parameters set to determine how tabular and geographic data are matched are 

set within the GIS software and may include spelling sensitivity of the match, address 

style, e.g., whether to match on address only or address and zip code, or whether to 

accept partial match scores. A match score denotes the number of address records 

from the tabular file that were located in the reference layer. Another parameter is 

offset distance, which is placing a data point a predetermined distance away from the 

original geocoded location. This may be done to place points on one side of the street 

segment or another to make the map more readable and/or realistic. 

These parameters are choices within the GIS software that will affect the 

geocode match rate. These preferences should be set and modified only after an 

examination of the tabular data. One should be completely familiar with the data in 

order to set these preferences. For example, if the spelling sensitivity parameter is 

lowered in a city that has two streets named Mill and Miller, inaccurate geocoding may 

result. 

Parameters set 

to determine 

how tabular and 

geographic data 

are matched are 

set within the 

GIS software... 

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Step Three: Geocode 


The common 

approach [in 

geocoding] is to 

place the 

address point 

along the street 

within the 

range of the 

street number. 

Once the parameters are set, geocoding is just a push of a button that starts the 

GIS software application’s geocoding process. Often, software packages use a fairly 

simple method to accomplish the actual placement of the tabular data in relation to the 

reference layer. The common approach is to place the address point along the street 

within the range of the street number. For example, this first table highlights one call 

for service at the address “292 Princeton Ave.” 

The following table depicts the data for the street reference layer and highlighted is the 

street segment in which “292 Princeton Ave” falls. 

When an incident is geocoded, the point is placed relative to a proportioned 

length derived from the ratio of the difference between the maximum and minimum 

address values and the physical length of the line segment. 

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For example, a segment may represent a street that is 100 yards long with an 

address range of 101 to 151 for the left side. An address of 125 would be placed 

approximately halfway down the line on the left side. Although this method usually 

misses exact real world coordinates, it is often sufficient given the detail of the street 

file and necessary resolution of the final map. In this example, “292 Princeton Ave” is 

located near the beginning of the street segment. 

As noted earlier, geocoding by street centerline may not be adequate to depict 

the exact location of an incident. In the case of mapping a few blocks of residential 

burglaries, one may want to geocode by parcel address. In some cases, such as 

recording traffic citations along routes that may not have readily discernable 

addresses, intersection address data can be recorded for later geocoding using street 

files. Intersection geocoding is often accurate to a higher resolution than street 

geocoding since there is no mathematical algorithm to define the physical location of 

the point generated; instead the point is placed at the center of the intersection of the 

appropriate line segments. However, even using intersection data to geocode is not 

completely accurate since, in reality, most incidents occurring at an intersection 

address do not occur exactly in the middle of where the two streets intersect. 

...geocoding by 

street centerline may not be 

adequate to 

depict the exact 

location of an 

incident. 

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A similar geocoding strategy uses polygons as opposed to previously discussed 

street centerline files. This method is the same as geocoding specific address data in 

that a value from the tabular data must match that of a geographic reference layer. 

For example, calls for service data often have a grid, beat, or district field in addition to 

an address field. In this case, the incident data has a Census block number field. 

When geocoding polygons, the grid, beat, or district value is geocoded to the center of 

the polygon that represents the grid, beat, or district layer. In this example, the Census 

block group layer matches that from the incident data. 

\ 

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Once the incident is geocoded, the point is placed in the exact middle of the polygon, as 

are all the points geocoded to that polygon. 

This type of geocoding is often used to create graduated color thematic maps by 

aggregating the data by polygon since data geocoded by polygon no longer can be 

located by address. However, many people geocode by address first and aggregate the 

data by polygon after the fact to avoid losing address data. Other types of geographic 

polygon data that can be used as reference layers for geocoding are zip codes, census 

blocks, census tracts, county, state, and country. Geocoding data at the polygon level 

is particularly useful when a dataset is very large or when address information is not 

as reliable as the grid, beat, etc. information. 

Step Four: Review results 

...many people 

geocode by 

address first 

and aggregate 

the data by 

polygon after 

the fact to avoid 

losing address 

data. 

Step four, reviewing results, is a matter of determining whether the geocoding 

process was successful and how successful it was. Most GIS software will have 

geocoding outcome statistics that indicate how many of the cases were successfully 

geocoded, how many are a partial match, and how many were not geocoded at all. 

Obviously, the ideal successful geocoding rate is 100%. Depending on the number of 

cases and the purpose of the analysis, a rate of 95% can also be acceptable. The 

important factor in accepting a geocoding rate less than 100% is understanding why 

some of the incidents are not geocoded. In some cases, missing data or data outside 

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The quality of 

these 

[geographic] 

layers will 

depend both on 

those 

maintaining the 

layers and 

growth rate of 

the jurisdiction. 

the mappable jurisdiction make up the incidents that are not geocoded. However, many 

times, there are other reasons that can and should be corrected. 

In the case of a street centerline layer, geocoding problems are generally 

manifested in the form of missing or incorrect address ranges or missing street 

segments. Street layers often lack address ranges for streets because of recent 

construction of new roads or errors in the original creation process of the reference 

layer. The quality of these layers will depend both on those maintaining the layers and 

the growth rate of the jurisdiction. For example, in a small town that has not added 

new streets in fifty years, the street reference layer would be easy to maintain, not 

only because nothing is being added but also because the town has relatively few 

streets to maintain. On the other hand, in a large city that is growing rapidly, the 

street layer would be much more difficult to maintain. 

Because street files are generally manually updated, they are also prone to data 

entry errors. The combination of these problems can be difficult to solve. Many 

agencies produce and maintain their own street centerline files or rely on their city or 

town’s engineering department to maintain them, and others have opted to purchase 

street centerline files that have been corrected and are bundled with contracts for 

regular updates. However, for layers particular to the police department, such as 

police district boundaries or beat boundaries, most likely someone at the police 

department will be tasked to maintain these. Fortunately, these layers are typically 

composed of many less geographic components than a street reference file. In any 

case, interagency cooperation can prove invaluable as a means for resolving geocoding 

problems. 

Even if the geographic reference layers are complete, there may still be 

problems with the tabular data used by law enforcement agencies, which stem 

primarily from having incorrect information or inaccurate data entry. Address errors 

in calls for service, crime, or accident data are often the source of much of the woes of 

geocoding in law enforcement and can be categorized into five common types: incorrect 

street numbers, street name errors, direction errors, incorrect intersections (in the 

case of intersection geocoding), and discrepancy errors. 

• 	 Street number errors can be the result of entry mistakes and are frequently 

identified as range errors; the address identified is either less than or greater 

than the address range of the corresponding records in the source file. 

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• 	 Street name errors can occur for a variety of reasons and are a result of the 

address record not matching the street name in the source database. These 

errors are among the most common, with reasons including misspellings, 

abbreviations, inconsistent street types, or lack of compliance with city 

addressing standards. 

• 	 Direction errors occur when the direction code of the address record does not 

match the direction code in the source database, either because they are 

incorrect or missing. 

• 	 Unmatched intersections can result from inaccurate intersection addresses or 

incorrect format. For instance, the intersection of Baltimore and Eutaw is 

referred to as “Baltimore & Eutaw” and will not be recognized by many GIS 

software packages if entered as “Baltimore/Eutaw” or “Eutaw & Baltimore.” 

• 	 Other errors can occur because there is a discrepancy between the common 

name of a location and the official address. For example, a police agency may 

have in its computer aided dispatch system a street called “Route 123,” but the 

official name in the street centerline file may be “US HWY 123;” thus, they will 

not match. 

Step Five: If necessary, respecify parameters and geocode again. 

Step five is only necessary when there is not a 100% geocoding rate, which 

seems to happen most of the time. Once the data have been geocoded and problems 

have been determined by the geocoding process, there are a few solutions. Some may 

choose to take care of the problems by changing the preferences, e.g. lowering the 

spelling sensitivity. However, as noted earlier, this should be done cautiously and with 

full knowledge of the tabular and geographic datasets, as changing preferences such as 

spelling sensitivity can lead to incorrect address locations. 

Another solution is developing alias tables, which allow for multiple names for a 

single entity. For example, a location such as a park or a mall may be referred to in a 

computer aided dispatch system as “Central Park” or “Centertown Mall” instead of by 

address to make them easy for dispatchers to enter. An alias table would replace the 

common name with the appropriate address in the GIS system so it can be located on 

the map. However, even though alias tables are helpful, it is still recommended that 

data be cleaned at the source to reduce confusion and facilitate consistency in data. 

Data are not only used for mapping purposes, so cleaning the data in the GIS would not 

solve data integrity issues when the data are used elsewhere. 

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The best way to correct data is to fix it at the source; in other words, bring the 

errors to the attention of those administering the computer aided dispatch system, to 

those maintaining the street centerline file, to the officers writing the reports, or to the 

clerks entering the data. However, this may not always be a realistic or a fast enough 

solution. In small projects or where a large number of cases share the same few 

mistakes, manual correction may be possible. Large datasets can often be corrected 

more efficiently when imported into a database or spreadsheet program (for example, 

Excel or Access) which has a “search and replace” utility. In addition, specialized 

software programs, referred to as “scrubbers” can be useful for large projects, and in 

instances where data are regularly imported. 

Conclusion 

These five steps outline the general process of geocoding law enforcement data. 

Because the types of data, problems, and solutions are common among law enforcement 

agencies, there is much to learn and share with one another. This overview has not 

detailed the specific methodology of geocoding in a particular GIS software program 

since the software used varies from agency to agency. For a specific outline of how to 

geocode in particular GIS software applications, see the text manual or electronic help 

files accompanying the software. 

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