Public Safety

Geography

A Quarterly Bulletin of Applied Geography for the Study of Crime & Public Safety Volume 2 Issue 4 | March 2011

Police Legitimacy and Predictive 

Policing

Tom Casady, Chief of Police

Lincoln Police Department

Lincoln, Nebraska

As law enforcement agencies have adopted computerized records management systems 

and geographic information systems, their ability to assemble and analyze data about 

crime and disorder has soared. Widely-available large data sets and new analytical tools are 

transforming policing. Our technological capabilities have grown faster than our capacity 

to understand and react to the ethical implications of these new capabilities. As placebased policing, hot spot policing, intelligence-led policing, and information-based policing 

merge into the science and practice of predictive policing, police will confront increasingly 

complex ethical issues. 

An excellent example of these issues concerns the relationship between income, housing, 

and crime. While the literature long ago established the nexus between poverty, substandard 

housing, and crime, geocoded crime data now allow police to visualize the relationship 

more clearly, and provides information so that the police can better deploy resources and 

target crime. Moreover, predictive policing principles suggest that given known factors,1 we 

can predict those areas where crime and disorder are likely to emerge. 

We also know more about people who are most likely to commit crimes. Parolees, 

probationers, and registered sex offenders have been identified in computer databases, and 

their homes, workplaces, and treatment centers can be geographically mapped. We can 

visualize, measure, and define concentrations of such past offenders. We can also predict 

who is at greatest risk for criminal behavior—unemployed young men, gang members, or 

chronic truants, for example. 

What police strategies emerge from such knowledge? Hot spot policing is one common 

outcome. If police predict that a certain neighborhood is headed toward a spike in crime 

and disorder, we may be tempted to apply the same kinds of strategies that have dominated 

crime reduction efforts in troubled neighborhoods in the past—zero tolerance enforcement, 

saturation patrols, high-visibility arrest warrant sweeps, or field interrogations. However, 

allocating law enforcement resources to areas predicted to have increasing crime and 

disorder is filled with ethical trapdoors. 

These kinds of strategies can create significant risks for differential policing based on 

income, age, race, immigration status, national origin, and other variables. Intensive 

policing of the activities of young men in poor neighborhoods is a recipe for deteriorating 

community relations between police and the community, a perceived lack of procedural 

justice, accusations of racial profiling, and a threat to police legitimacy.

Contents

1 Police Legitimacy and 

Predictive Policing

2 The Predictive Policing 

Symposium: A Strategic 

Discussion

3 Proactive Policing: Using 

Geographic Analysis to 

Fight Crime

6 Experimenting with FutureOriented Analysis at Crime 

Hot Spots in Minneapolis

9 Geospatial Technology 

Working Group (TWG): 

Meeting Report on 

Predictive Policing

11 Technical Tips

14 News Briefs

15 Geography and Public 

Safety Events
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G&PS | March 2011

How can predictive policing empower enforcement, graffiti removal, expanded 

policing strategies that minimize this ethical swimming pool and library hours, and other 

conundrum? community activities. 

The answer lies in broadening the choice of Moreover, police should focus on building 

police strategies when dealing with those places relationships with other stakeholders in these 

where law enforcement can predict crime and areas. Working collaboratively to enhance the 

disorder. Rather than relying solely on a “cops- collective efficacy2 of a neighborhood and to 

on-dots” approach, police departments need prevent crime is far less likely to contribute 

to create strategies that change the conditions to a schism between the police and residents 

of the potential crime environment. Problem- than crime suppression and law enforcement 

oriented policing projects in areas identified activities alone. 

as crime-prone, for example, may be able to The knowledge gained from modern address issues such as litter, truancy, or liquor technologies should be used to advance license density and operations. strategies in policing that ameliorate crime and 

Rather than using our growing knowledge disorder without participating in overzealous 

of where crime is likely to occur to guide policing, racial profiling, and ageism. As 

crackdowns on hot spots, maybe we can predictive policing evolves, we will need a 

use that knowledge to empower prevention constant focus on assuring and preserving 

strategies—or at least to add prevention police legitimacy as we seek to intervene in the 

strategies to law enforcement’s repertoire. causal chain of crime and disorder.

Neighborhoods where crime occurs are 

often the ones that most need recreational Notes

opportunities, mentor programs, community 1. Such as housing density, population density, age, 

organizing, lever-pull strategies, and youth percentage owner occupied dwelling units, single 

sports programs. These areas must be parent households, and average income.

designated as a priority for the limited public 2. Collective efficacy is a people’s willingness and 

dollars available for municipal services such mutual trust to work for the common good of a 

neighborhood. as park maintenance, curb repair, codes 

The Predictive Policing Symposium: 

A Strategic Discussion 

Modern policing, even with the law enforcement, and many policing experts 

development of information-based and believe that it may be a prominent direction in 

mapping technologies, has been largely reactive the future. 

rather than proactive. Rather than working The first Predictive Policing Symposium to anticipate new crimes, officers often patrol was held in November 2009 in Los Angeles, locations where crimes have been already California. The symposium, which was hosted been committed. With recent technological by the National Institute of Justice (NIJ) advances, software systems can now use and the Bureau of Justice Assistance (BJA), advanced algorithms to allow police agencies brought together researchers and practitioners to predict locations where a certain type of to discuss the concepts involved in predictive crime is likely to occur and direct appropriate policing. They examined how using analytic resources to those areas. This effectively stops strategies could affect how crime will be crimes before they occur. Recent initiatives monitored and prevented in the future. Specific using this “predictive” approach have shown focuses included: defining predictive policing, great success. As a result, predictive policing discussing its current use in the field, examining has made its way to the forefront of strategic its implications in terms of privacy and civil 
3

liberties, discussing current research predictive policing may encroach on civil listings, and city planning information. 

projects, and assessing challenges. These liberties, using information in a way that Moreover, crime analysts should work to 

focuses are discussed below: violates the Constitution. Therefore, incorporate proven criminological and 

police must carefully determine what crime prevention theories into predictive Defining predictive policing. Predictive kinds of information are protected and policing to help broaden and solidify the policing, as defined by NIJ’s Deputy how information can be legally shared predictions. Director of the Office of Science and or published. Conference participants Technology, John Morgan, refers to “any In sum, conference participants showed suggested that departments must keep policing strategy or tactic that develops and enthusiasm for predictive policing their processes transparent, and must uses information and advanced analysis to initiatives, and many feel that this kind of communicate regularly with the public if inform forward-thinking crime prevention.” strategy can transform the policing field in they want to ensure that the community Experts at the conference examined this the future. As predictive policing tends to accepts and supports predictive initiatives. definition, suggesting that predictive concentrate resources in areas of greatest 

policing must be balanced with intelligence- Current research projects. NIJ sent out a need, it may be an excellent strategy for 

led policing and community policing, request for proposals for predictive policing departments who face limited financial 

particularly until the criminal justice system projects in March 2009. A number of police resources in the current economic crisis. As 

develops better tools and research databases. departments across the country were selected, a follow up to the conference, NIJ planned 

Police who engage in predictive analytics and will develop predictive policing projects. to work with grantees in early 2010 to 

must keep safety, crime reduction, and A group at RAND Corporation will evaluate discuss the projects that had been funded 

quality of life in mind. the projects. A list of the grantees and their and initiate work. NIJ hopes to bring 

awards is available at: www.ojp.gov/funding/ the results of the projects to the table for Use in the field. Currently, predictive pdfs/FY2009221.pdf. discussion at a future conference. policing has been used for crime 

mapping, data mining, geospatial Challenges. Predictive policing faces a This summary is based on:

predictions, and social network analysis. number of challenges. One main challenge Uchida, Craig D. A National Discussion on 

In the future, panelists suggest it be used is determining how to compile valid and Predictive Policing: Defining Our Terms and 

for managing budgets and personnel, reliable data and measurements. Police Mapping Successful Implementation Strategies.

monitoring offenders, and planning safe analysts must understand what data can Washington, D.C.: U.S. Department of 

and economical neighborhoods. complement a predictive analysis, how to Justice, National Institute of Justice, 2010. 

obtain access to that data, and how that NCJ 230404. Issues of privacy and civil liberties. data can best be integrated into a successful Conference participants expressed concern Access the full report at: www.ncjrs.gov/ analysis. Examples of useful data include that the general public would think pdffiles1/nij/grants/230404.pdf. census data, public health data, foreclosure 

Proactive Policing: Using Geographic 

Analysis to Fight Crime 

Colleen McCue, PhD

Law Enforcement Program Manager

SPADAC

McLean, Virginia

I

n an analysis of police interventions clusters.”1 In other words, knowledge and of information-based approaches to 

designed to reduce violent crime insight regarding when, where, and what prevention.2 This work was conducted 

conducted by Dr. Cynthia Lum and her type of crime to expect can be leveraged in the public health/emergency medical 

colleagues, Cody Telep notes that “[t] into more effective, proactive, and targeted response setting, but researchers also 

he most effective police strategies are approaches to crime prevention. believed that there was potential value for 

focused and highly proactive, relying the public safety community. The results Several years ago, researchers at the on crime analysis...police tend to be of this early research were promising Medical College of Virginia began to particularly successful when tailor-made and underscored the value of advanced explore the use of statistical modeling to efforts are concentrated on specific high analytics when modeling complex characterize violent crime and in support violence street blocks, corners, and address problems like violent crime. It also 
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G&PS | March 2011

showed how advanced analytics can support On New Year’s Eve in 2004, the PSN Team 

information-based approaches to treatment tested their strategy, now called “Risk-Based 

and prevention. The immediate value to the Deployment,” on a model based on incidents 

public safety community, particularly in the of random gunfire.4 Their goal was to create a 

operational environment, was less clear. model of crime and proactively place resources 

when and where those resources were likely Sensing both interest and promise, these to be needed so that they could prevent crime researchers began to work closely with the and respond to incidents more rapidly. The law enforcement community in an effort to results demonstrated a 47 percent reduction translate this research to law enforcement in complaints for random gunfire and a practice; to use statistical models to support 246 percent increase in weapons seized. The police operations and responses. Visualizing efficient resource allocation also required fewer the models in a spatial environment helped personnel assets, saving $15,000 during the law enforcement make informed deployment 8-hour initiative. decisions, significantly increasing the value of 

this work. Using maps to depict the statistical models 

turned out to be game changing. Not only This early law enforcement research was could researchers better convey the “when, supported by Project Safe Neighborhoods where, and what” of crime in that environment, (PSN), and focused on gun-related violence. but this method also allowed law enforcement One of these first projects involved creating officers to easily understand and interpret a model for robbery-related aggravated complex statistical relationships and to provide assaults.3

 The PSN Team developed models ideas about how to support this style of crime that helped determine what caused an prevention and response. armed robbery to escalate into an aggravated 

assault. These models could then be used to 

address this crime pattern through proactive How Geospatial Statistical 

deployment strategies and to influence public Analysis Works 

safety outcomes in the community. To illustrate the difference between traditional 

The most obvious finding from this first density mapping and geospatial statistical 

exercise was a marked difference between analysis, a series of auto parts thefts from 

the location of armed robbery incidents and vehicles have been analyzed, depicted visually, 

the areas associated with a higher risk for and compared. Hot spot or density mapping is 

a robbery-related aggravated assault. If the used frequently in law enforcement to visualize 

goal of deployment is to proactively allocate locations where crime incidents have occurred. 

police resources when and where they likely Geospatial statistical analysis, however, 

to be needed (through either law enforcement characterizes the locations associated with past 

presence or rapid response to incidents), then events and creates a model that incorporates 

deploying based on the frequency and spatial environmental factors statistically associated 

distribution of armed robberies would result with past incidents. This model can then be 

in police assets being in the wrong place at used to identify similar locations where future 

the wrong time if the objective is to prevent incidents are likelier to occur. Ultimately, 

robbery-related aggravated assaults. this approach enables law enforcement to act 

proactively to prevent crime and influence 

outcomes. Testing the Model 

Although the results of the research on armed Figure 1 shows known incidents of auto parts 

robberies generated considerable enthusiasm, thefts (black dots), areas associated with an 

the researchers needed to determine whether increased likelihood for a future incident (dark 

this approach worked in practice and wanted to areas), and auto theft incidents that occurred 

demonstrate its value. after the model was created (triangles).
5

In this particular analysis, thieves stripped incidents would have been missed. Using statistical models to new spaces supports 

vehicles of valuable auto parts.5 Law geospatial statistical analysis, analysts can an information-based response. Law 

enforcement wanted to identify the identify areas statistically similar to locations enforcement can use this information to 

locations associated with future incidents where prior incidents occurred. These create solutions suited to a particular crime 

to deploy resources more accurately, new areas would not be identified using series, pattern, or cluster, and ultimately 

prevent crime, and catch perpetrators. traditional methodologies. keep communities safer. 

Figure 1 illustrates the known events In addition to depicting complex crime- (shown as black dots), and the area that Notes environment relationships, these approaches statistical modeling suggests may be 1. Telep, C.W. 2009. Police interventions help law enforcement understand the factors associated with future incidents (the to reduce violent crime: A review of associated with crime incidents. Certain red areas). As the figure shows, the area rigorous research. Presented February 3 at 

environmental factors attract or enable Congressional briefing: “Reducing Violent associated with an increased likelihood crime, while other features may serve as Crime at Places: The Research Evidence,” for future events includes the original deterrents. These factors can be ranked Washington, D.C.

incidents, but also extends well beyond based on their relative contribution to the 2. McLaughlin, C.R., J. Daniel, S.M. Reiner, the area associated with the original series. likelihood of future incidents and used for D.E. Waite, P.N. Reams, T.F. Joost, J.L. 

The green triangles illustrate incidents Anderson, and A.S. Gervin. 2000. Factors analysis. This factor analysis provides unique that occurred after the original model was associated with assault-related firearms injuries opportunities for information-based or created, and thus validate the model. in male adolescents. Journal of Adolescent 

“tailor-made” crime prevention. Health 27:195–201.

Figure 2 includes all incidents and the 3. McCue, C. and P.J. McNulty. 2004. Guns, In essence, approaches using geospatial geospatial statistical analysis, as well as drugs and violence: Breaking the nexus with statistical analysis allow law enforcement traditional density mapping, to further data mining. Law and Order 51:34–36.

to proactively prevent and disrupt crime. illustrate the difference between the two 4. McCue, C., A. Parker, P.J. McNulty, and D. The ability to identify and characterize methods of geospatial analysis. By deploying McCoy. 2004. Doing more with less: Data 

threats and anticipate crime represents a mining in police deployment decisions. Violent resources only where previous incidents have game-changing shift in law enforcement. Crime Newsletter 1:4–5.

occurred or by employing standard density Ultimately, the ability to characterize the 5. The author thanks David Grason at SPADAC mapping techniques, other areas associated environment, identify factors associated for the example.

with an increased likelihood for future with known incidents, and apply these 

Figure 1. Map of auto theft incidents. Figure 2. Comparison between a traditional density map and 

geospatial statistical analysis.
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G&PS | March 2011

Experimenting with Future-Oriented 

Analysis at Crime Hot Spots in Minneapolis

Sgt. Jeff Egge

Minneapolis Police Department

Minneapolis, Minnesota

Police leadership around the country Figures 1 and 2 show examples of initial is beginning to advance the idea of attempts by the MPD Crime Analysis Unit to 

predictive policing, a policing strategy that react to crime incidents that occur in patterns. 

uses information and advanced analysis to Figure 1 displays an analysis of the next 

inform forward-thinking crime prevention. likely armed robbery in a series of fast-food 

Once this concept has been subjected to restaurant holdups in 2009. The limitation 

rigorous experimental evaluation, predictive of this metropolitan-areawide prediction is 

policing has the potential to focus resources the uncertainty of complete data sets beyond 

proactively to reduce crime. jurisdictions. Nonetheless, the analysis found a 

predicted regression point within a half mile of Crime analysis in Minneapolis, Minnesota, the next robbery. Unfortunately, that prediction originated in the wake of several evidence fell far outside the city limits. based research projects by noted criminologists 

Lawrence Sherman and David Weisburd in Figure 2 illustrates the use of predictive 

the 1980s. When a COMPSTAT program was analytics to develop a list of potential targets for 

instituted in the 1990s, it led to a 34 percent a robbery spree. On being released from prison, 

reduction in crime in the following decade. the suspect planned to rob small boutique 

The Minneapolis Police Department (MPD) is businesses or laundries where lone females 

currently working with predictive policing as a worked without video surveillance.

way of identifying potential crime locations and In both cases, MPD analysts attempted to allocating resources to prevent crime. translate contemporary evidence-based research 

The foundation of Minneapolis’s predictive into actionable knowledge through advanced 

policing efforts is a report management system analysis, data mining, and considering the 

created 20 years ago, that has become the factors that affect crime. They created the 

driving force behind the weekly CODEFOR following formula to explain predictive policing 

(COMPSTAT-like) meeting. One important analysis: the crime triangle (suspect/victim/

attribute of CODEFOR is that it provides an location) multiplied by x/y factors (i.e., the 

opportunity for several levels of leadership to factors that affect the type of crime being 

use crime analysis and participate in improving analyzed) equals crime prediction.

public safety. The Minneapolis Crime Analysis MPD recently used this formula to create Unit has been conducting predictive policing 1 patrol zones to reduce gun violence. Analysts research in exploratory applications. This identified three layers of proximity to micro article presents the results of this research and hot spots. The first layer was based on places discusses the value of predictive policing. where suspects discharged weapons. The 

second identified places where suspects were 

Early Applications of Predictive more prone to be arrested with guns. A third 

Policing layer identified the places where victims were 

Many experienced crime analysts feel predictive shot or shot at. Analysts captured data for the 

analysis is a natural evolution of crime analysis analysis layers by data mining in places where 

methods, which increasingly uses analytic gun violence historically had occurred and 

thresholds and statistical forecasting to identify factoring those data with recent spatial trends 

patterns, trends, and anomalies. in each criterion. 
7

Figure 1. Analysis of potential armed robber activities.

Predicting Crime in Specific 

Places: Putting Theory Into 

Practice 

Research has shown that hot spots policing 

effectively reduces violent crime. A recent 

study by the Police Executive Research 

Forum (PERF),2 for example, identified 

the effectiveness of problem solving and 

situational crime prevention in reducing 

street violence in hot spots. Earlier research 

by Sherman, Gartin, and Buerger3 showed 

that in Minneapolis and other cities 5 

percent of addresses produced nearly 100 

percent of the calls for police service for 

predatory violent crimes such as robbery 

and rape. Sherman4 also concluded that 

future crime is six times more predictable 

by address than by individual, which gives 

credence to the theory of place-based 

predictive policing. 

MPD wanted to create a hot spot analysis 

that was easy to understand and apply. 

Analysts considered common elements 

between crimes, connected patterns, and 

available data. For analysts to predict the 

trajectory of crime accurately, they must 

understand the patterns that indicate a 

higher risk of victimization or danger. They 

must be able to distinguish trends from 

anomalies. 

Thus, to put predictive policing into 

practice, MPD started by mapping data 

using accurate x and y coordinates (or 

geospatial markings). The analysts then 

worked to capture high-risk offenders 

by examining the locations of suspects, 

victims, the associates of both, and arrests.

To improve the consistency and 

predictability of the mapping, analysts 

compared the maps to locations of problem 

addresses, parks, and street corners. 

Specifically, they used Structured Query 

Language queries of police reports created 

following Sherman’s last Minneapolis study 

of repeat call addresses, aligning maps 

from the current study with the problem 

addresses and places they had identified 

earlier, in an effort to predict the locations 

of violent crime. 

Figure 2. Analysis of potential targets for a robbery spree.
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G&PS | March 2011

Analysts then attempted to localize crime to The COMPSTAT response to aggregate crime 

micro hot spot grids that could be monitored spikes has often been described as “whackby a single patrol car. Once probable patterns a-mole,” for the board game where a mallet 

had been isolated into manageable one-, (traditional police tactics) is used to strike at 

two-, or three-block areas, a report was given moles (crime and criminals) emerging from 

to patrol supervisors. The report included a holes (places). In order to promote more 

map, recommended times for intervention, sustained interventions and reductions in 

problem persons in the geographic area, and crime, MPD strives to discuss and engage in 

other facts that could improve an officer’s predictive policing tactics during COMPSTAT 

situational awareness. meetings, with the view that predictive 

analysis can lead to safer neighborhoods. MPD then examined outcomes and 

consequences of the initiative to determine Moreover, police must improve information 

whether predictive analysis improved sharing. For predictive analysis to best 

police intervention. This was a particularly analyze crime trends, patterns, and 

important part of the project—because the anomalies across jurisdictional boundaries, 

mission of contemporary police is based on crime analysts need to be able to transcend 

reducing crime and improving public safety. longstanding silos, sandboxes, and 

MPD’s research illustrates the success of intelligence hoarding in the police sworn 

proactive and focused problem solving by ranks and within political boundaries. 

police using predictive hot spots analysis. 

One example of MPD’s successful analysis is Conclusion 

illustrated in Figure 3, a geographic analysis Predictive analysis involves anticipating 

of violent street corner gangs. Over the last 5 questions. Questions lead to the search for 

years traditional gangs in Minneapolis have evidence, evidence helps officers establish facts, 

been replaced by small, splintered street-corner and facts in turn support and substantiate 

cliques. These gangs at first appeared to be action. Throughout the process, officers must 

random, because members go in and out of ask, “How can this be made better and can we 

incarceration or may be incapacitated, so show the results?”

intelligence efforts had been mostly reactive. Police must keep moving the science forward, Over time, however, the apparently random making predictions, and acting on the results. and opportunistic patterns became geographic The goal should always be to reduce crime and incidents, which could be identified as place- improve service. based behaviors. Thus, these behaviors could 

be anticipated and predicted. MPD is currently Notes using this analysis to make more accurate 

predictions that identify zones for focused and 1. Taylor, Bruce, Christopher S. Koper, and Daniel 

J. Woods. 2010. A randomized controlled trial of proactive policing, in order to reduce robbery different policing strategies at hot spots of violent and illegal weapons and increase traffic stops. crime. Journal of Experimental Criminology.

MPD hopes to use this kind of prediction to 2. Police Executive Research Forum. 2008. Violent 

put cops on the dots of the places where gangs Crime in America: What We Know About Hot Spots 

are active and to stop crime. Enforcement. Washington, D.C.

3. Sherman, L.W., P.R. Gartin, and M.E. Buerger. 

Predictive Policing as a Part of 1989. “Hot Spots of Predatory Crime: Routine 

Activities and the Criminology of Place.”

COMPSTAT Criminology 27:27–56.

To conform to the needs of COMPSTAT and 4. Sherman, Lawrence. 1995. Hot Spots of Crime 

similar strategies, police management must and Criminal Careers of Places. In Crime and 

Place: Crime Prevention Studies, vol 4, ed. John Eck balance resources between historically chronic and David Weisburd, 35–52. Monsey, New York: violent hot spots and statistics based on the Willow Tree Press.

current ebb and flow of crime. 
9

Figure 3. Violent Crime Density Involving Gang Members or Associates, 2009.

Geospatial Technology Working Group (TWG): 

Meeting Report on Predictive Policing 

Introduction Furthermore, the Geospatial TWG helps officers face, what tools and technologies 

T determine grant funding priorities, help officers identify crime, and how he Geospatial Technical Working identify concerns in the field, and review predictive policing can be incorporated into Group (TWG) is a committee of the progress of existing grants. future strategies. practitioners, applied researchers, and 

academics supported and organized by the The Geospatial TWG meets bi-annually. 

National Institute of Justice (NIJ). The As part of the Fall meeting, the TWG Defining Predictive Policing 

Geospatial TWG specifically works with spent several hours discussing the topic of The TWG members defined crime 

NIJ’s Mapping and Analysis for Public predictive policing. Specifically, the TWG prediction in two ways. First, prediction 

Safety (MAPS) program in order to help discussed different aspects of predictive describes a forward-looking effort that 

determine criminal justice technology policing, including how geographic analysis assesses risk of broader, long-term trends. 

needs specific to geospatial technologies. assists in predictive policing, what challenges Second, prediction addresses short-term 
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G&PS | March 2011

factors that can cause crime to occur. As such, Technology’s Effect on Crime 

predictive policing identifies not just crime Predictive policing efforts must understand incidents, but the factors that lead to them, and how advancing technologies can affect the trends they initiate. crime. Researchers and practitioners should 

examine the risks of the new technology. This 

Identifying Challenges knowledge can predict how technology can 

The TWG members identified a number of or will be used for criminal activity or how 

desirable technology products can become challenges officers face when implementing targets of theft. Changes in technology can predictive policing efforts: have a profound and immediate effect on crime  Limited resources. Budget and staffing opportunities and modus operandi. constraints can affect an agency’s ability to 

collect relevant data, implement effective 

intervention/prevention strategies, provide A Predictive Policing Toolbox 

analysis, and research the outcomes of new The TWG ended the session by making 

strategies. suggestions for a predictive policing “toolbox” 

 Political pressure. that would provide a flexible framework for each The political pressure agency to develop its own methodology. For on police departments to lower the instance, the TWG suggested that departments crime rate and show immediate results 

could: is not always conducive to the more 

methodologically rigorous evaluation 

 Identify data from other agencies (e.g., 

process that predictive policing requires. schools and hospitals) that may be useful 

 for predictive policing analyses. Information management. Departments 

may be asked to increase data sharing. Some 

 Create predictive policing task forces.

departments may feel pressured to provide 

 Create Memorandums of Understanding data in a different format or with levels (MOU). of consistency they have not previously  Develop or enhance software for use in achieved. 

predictive policing.

 Data overload. Some agencies might feel 

 Examine qualitative and quantitative data overwhelmed by the amount of data they during analysis. collect because of new technologies and 

procedures.

 Create guidelines on how to make use of 

 Data quality. the predictive outcome. Data should be timely, 

accurate, and reliable.

 Improve practices for collaboration across 

 Adaptation. local, state, federal, and international law Predictive policing approaches 

must be adaptable and responsive to enforcement agencies.

changes in a department’s operational 

environment, new agency policies or Conclusion

directives, and community demographics. Predictive policing must combine an analysis 

of short-term activities and long-term trends to 

Unit of Analysis identify the locations where crime may occur in 

a community. Agencies should focus on using Police departments who wish to begin using predictive methods to prevent crime. While predictive policing will not benefit from a predictive policing may represent a decisive one-size-fits-all approach. No standard unit of paradigm shift in the law enforcement field, analysis can be used to make predictions for agencies must focus on refining existing practices all communities. As such, police must identify and developing new techniques to examine the and refine units of analysis in clear and precise data that already exist. ways. The TWG recommended that predictive 

policing efforts focus on improving processes for 

developing units of analysis that would enable 

more precise data examination and prediction. 
11

Predicting Demand for Service for Future Developments 

Philip Mielke

GIS Supervisor

Redlands, California

When police management wants to Incident Data understand where officers spent time Analysts should work to acquire the best 

or needs to predict how a new housing or assessment of incident data, which may 

business development will require a need for come from a combination of Computerpolice service, analysts must determine how Aided Dispatch (CAD) systems or the 

much time officers spend per incident, by agency’s Records Management System 

location. This type of analysis can help assess (RMS). The analyst should to be able to 

development impact fees, which allows a join multiple officer time-signatures2

 per 

police department to voice considerations or geocoded incident. Make sure that incident 

concerns about the city’s growth policy. This data are geocoded with an offset3

 because 

article guides an analyst through preparing land use data may be subdivided by parcels 

data, joining data, summating input data, or street centerlines. Incident data must be 

and interpreting the results. attributed to the correct land use. 

Data Preparation Time Spent Data 

Analysts must create a database of the time An analyst must prepare three kinds of data: each officer spends on each call, from time 

 Land use data. of assignment to the time when the officer 

 Incident data. left or closed the incident. These data can be 

a challenge to pull from any RMS or CAD.  Time spent data. Every system can be different, but the analyst 

should account for as much time spent in Land Use Data an area as possible. Create a database with The best source for land use data is the city’s fields collecting times for when the officer planning department or regional land use was assigned (or en route to the scene), when planning commission. These organizations the officer arrived, and when the officer left may also have information on zoning 1 or closed the incident. If multiple officers layers, and/or other types of land use or responded, those time signatures should related data, such as zoning data or general be contained in separate fields for the same planning data. Research what the differences incident number. 

are. Keep in mind what each layer represents 

in the real-world scenario, and decide “Time spent per officer” can be discerned 

whether a land use layer may be more through a series of field calculations 

accurate or timely. (Officer1closetime – officer1enroutetime), 

and “total time spent” can be calculated Zoning and general plans can represent how by summing the fields containing “Time the city intends to grow with time, but these spent per officer.” The analyst may need to may not accurately depict the present reality. account for officer-initiated incidents where 

If a city has a GIS department, they will there may not be an “officer1enroutetime” likely maintain this layer of information and value, and replace it with the proper time can describe the timeliness and accuracy of signature. All of these data need a common the data. Ultimately, if an analyst needs to ID to perform a join from the time spent determine what kind of demand for service database to the incident data. 

a new development will bring, a standard 

land use layer is best for the study. 

Process 

Step 1: Join the time-spent database to 

the incident feature class. 

 Right-click on incident feature class. 

 Click “Joins and Relates >”, and then 

“Join...”. The following dialogue box 

should appear:

 Join the time spent database to the 

incident data, and use the common 

identifier to make this join. For the first 

dialogue, “What do you want to join to 

this layer?” select “Join attributes from 

a table.” 

 For the following dialogues, select the 

field on the incident database that is 

the common identifier, select the time 

spent table, and then select the field 

on the time spent database that this 

the common identifier. Select “Keep 

all records” under “Join Options.” 

This will allow you to check the data 

TECHNICAL TIPS
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G&PS | March 2011

to make sure the entirety of each dataset 

matches the other. Right-click the incident 

data. The time spent fields should be 

joined to the incident data. You should 

be able to scroll to the right side of the 

database to see information in all fields for 

all records. 

Step 2. Spatially join4 incident data and the 

joined time spent database to the land use 

layer. 

 Right-click on the land use layer in 

ArcMap’s table of contents. 

 Select “Joins and Relates >” and then 

“Join...” This will bring the join dialogue 

to the screen (see figure below).

 Change the initial parameter to “Join data 

from another based on spatial location.” 

This will bring a different set of parameters 

to the join dialogue box. 

 Choose the Incident layer that was used 

for the tabular join for step 1. This 

will be a “points to polygon” spatial 

join, meaning that the point data can 

be summarized by the polygons that 

contain it. A “count” field is automatically 

created, and the analyst also has the 

option to produce the average, sum, 

minimum, maximum, standard deviation 

and variance for every numeric field. 

Ultimately, this process will determine the 

sum of the ‘total time spent’ per incident 

field, and this sum will be calculated for 

each polygon of the land use layer. 

 Identify where the new layer should be 

saved, and click “OK.” 

Step 3. Create a sum table from the outputs 

of step 1 and step 2.

 The resulting attribute table should have 

the sums of time spent by incident per 

land use polygon. The analyst can produce 

a choropleth map5 on the resultant ‘time 

spent’ field to depict the data and check 

for outliers. Check whether any land use 

types that seem like they are receiving an 

inordinate amount of time. Identify any 

large ‘public and institutional’ land use 

types that may have an excessive amount 

of incident geocoded to police stations 

because of faulty address reporting. If data 

accurately represent where time is being 

spent by field officers, the following sum 

table operation will yield “time spent” per 

acre of “land use type.” 

 Right-click the resulting feature class from 

step 2 and select “Open Attribute Table.”

 Right click on the “land use type” or 

category field and select “Summarize...” 

The following dialogue will appear:
13

 The “Select a field to summarize:” 

dialogue should already be populated 

by the previous step. Three fields 

should be summed: the resultant 

spatial join sum of the “total time 

spent” field, the “Shape_area” field, 

and the “Count_” field. 

 Select the numeric “Sum” function 

by scrolling through the fields and 

expanding the numeric functions. This 

requires clicking the “[+]” left of the 

three fields. Specify the output table 

name and location and click “OK.”

 To finalize this sum table you must 

convert area units. It is likely that the 

coordinate system you are working 

with is in some form of “State Plane” 

coordinate system, and the base unit 

of measurement is in feet. In order to 

standardize the ratios of “Time spent 

per land use type per acre,” square feet 

should be converted to acres. 

 Under the “table options” icon on the 

top-left of the sum table,6

 select “Add 

Field...” 

 Select “Short Integer” for the ‘Type.’ 

Enter “Acres” for the name. Enter a 

precision of two. One acre is 43,560 

sq. ft. This measurement can be used 

to convert sq. ft. to acres. 

 Right-click on the “Acres” field and 

select “Field Calculator...” 

 In the “Acres=” dialogue, enter “Sum_

Shape_Area”/43560 and click “OK.”

Interpreting the Results 

The resulting summarization table provides 

the analyst with information about the 

relationship between land use types, area, 

number of incidents, and time spent per 

land use type. Each land use type may 

influence the type of incidents that will 

occur in the area. For example, commercial 

land uses are a prerequisite for commercial 

burglaries or shoplifting, and the amount 

of time required to handle incidents varies 

by the crime type (and ultimately by the 

requirements unique to each incident). Add 

another field and use the field calculator to 

represent the time spent per acre.

The “Create Graph Wizard” can depict the 

ratio of time spent per acre by land use. To 

use it, follow these instructions:

 Click the “Table Options” icon in the 

top-left of the sum table, and click 

“Create Graph...” The following wizard 

dialogue should appear: 

 Select ‘timeperacre’ as the “Value field” 

and select the appropriate land use 

type for the Label Field. This shows 

the relationship between a land use 

type and the amount of time that it 

takes to respond to incidents in these 

types, by area. 

The ratio that is calculated allows the analyst 

and city staff to predict the demand for 

police service when a new development is 

proposed. Development impact fees can 

be assessed and justified using this process, 

and administrative time per field officer 

should be determined by the jurisdiction. 

Managerial decisions can be improved if 

management can quantitatively see where 

officers spend time. 

Police can determine how department 

services will be affected after city 

developments have been built if they analyze 

the resources police commonly allocate by 

land use type. Analyzing crime location 

ultimately helps officers decide on tactical 

and strategic patrol initiatives. Combining 

location and timely resource allocation gives 

governing bodies an opportunity to better 

understand the impacts of the decisions they 

make, and this allows police the ability to 

justify service level predictions. 

Notes

1. Zoning data is a GIS layer that identifies what 

developers can build in a certain area.

2. Computer-aided dispatch systems store 

multiple time signatures for when an officer is 

assigned to a call, is en route, has arrived, and 

is closing the call. 

3. Offsets in geocoding occur when geocoded 

points are placed a certain distance from the 

street, and not on the street itself. 

4. The “Spatial Join” function is a very useful 

tool for crime analysts. It allows incident 

data to be summed by polygons, and for 

choropleth maps to be produced. Risk models 

can be developed by joining incident data 

to census data and discerning the number 

of “crimes per population.” In this use, the 

analyst determines the amount of time spent 

by officers in the field based on land use. This 

amount is used to determine the necessary 

ratio of time spent per acre based on land use. 

This calculation can then be used to determine 

future service demands or cost of service by 

future land use development.

5. Choropleth maps add the total number of 

incidents in polygons.

6. This is a new location to access table options 

in ArcGIS Desktop 10. 
1414

G&PS | January 2011

Transitioning to the As the world moves away from the 2008 

recession, law enforcement must work 

Age of Predictive to find the best strategies to create safe 

neighborhoods and budget wisely. Predictive 

Policing policing helps maximize the use of available 

resources. In today’s limited economic conditions, many 

police departments must learn to deploy For more information, see: 

resources more effectively to save both time Beck, Charlie, and Colleen McCue. 

and money. As police management works to “Predictive Policing: What Can We Learn 

make each agency more efficient, predictive from Wal-Mart and Amazon About 

policing strategies have emerged as a way to Fighting Crime in a Recession?” Police Chief 

optimize scarce resources, targeting crime Magazine, 2010.

before it happens.

Predictive policing has been described as Chicago Police the next era in policing, evolving from 

intelligence-led policing, which is a Department Adopts 

modern vision emphasizing research-based 

decision making, information sharing, Predictive Crimeand accountability. Predictive policing, 

as pioneered by the Los Angeles Police Fighting Model 

Department, uses analytic technology and In April 2010, the Chicago Police new algorithms to analyze crime patterns, Department began piloting a crime predict locations where similar crimes may prevention strategy called predictive analytics. occur, and deploy patrol cars and other Predictive analytics uses advanced analysis resources to fight crime preemptively. and mathematical algorithms to determine This strategy comes from e-commerce locations where crime is likely to occur. The and marketing, which have learned to use department deploys patrols to these locations analytic, intelligent methods to predict what to deter crime and respond effectively to consumers might want to buy. A common need. 

example of this strategy is used by Amazon. The department has been partnering with com with the phrase, “Customers who a local university, Illinois Institute of bought this item also bought....” Similar to Technology, to create a predictive policing this style of marketing, predictive policing model. Officers have also created an analysis determines how one crime may affect similar group. Thus far the new strategy has shown crimes in the future. It identifies trends, 

positive results in reducing crime and patterns, and relationships found in data targeting areas where crime will occur. associated with criminal behavior or activity, 

and uses that information to deploy resources For more information, see: http:// and affect policy. abclocal.go.com/wls/story?section=news/

local&id=7599221. Predictive policing strategies have been 

successfully used to reduce gunfire complaints 

on New Year’s Eve by nearly 50 percent, 

prevent violent crimes, and link a number Albuquerque Police 

of DNA cold hits with burglaries. However, 

use of this approach in Los Angeles is Use Predictive 

revealing that no one approach, technology, Policing to Target or algorithm will universally address all of law 

enforcement’s challenges. Police departments Car Thefts 

across the country must work to match In anticipation of the popular Balloon Fiesta, individual solutions with specific problems. the Albuquerque Police Department has been 

using predictive modeling to target car thefts 

at the festival.

NEWS BRIEFS
15

Officers have planted cars in places 

that algorithmic predictions suggested 

may be prime locations for theft, and 

plan to monitor these locations for 

thieves. License plate scanners, mounted 

throughout the city, will instantly tell 

officers when a car has been stolen, so 

police can send an immediate response. 

Police hope that these predictive, analytic 

techniques will help them ensure that no 

cars are stolen this year. 

www.kob.com/article/stories/S1753167.

shtml?cat=500

Predictive Policing 

Helps Tennessee 

Officers Reduce 

Violent and 

Property Crimes 

Use of a new policing strategy in Memphis, 

Tennessee, has helped lower the rate of 

violent, property, and UCR Part I crimes by 

an average of 15.8 percent. This decreasing 

crime rate has come without an increase in 

the need for officers.

The reduced crime rate comes from a 

strategy known as predictive policing, 

which uses advanced analytic software 

to predict locations where crimes may 

occur. In this way, police can stop crime 

proactively rather than simply reacting to 

crimes as they occur. 

Departments across the country, like the 

one in Memphis, have been installing this 

analytic software, which can cost as much 

as $100,000. Many hope that the change 

from reaction to prediction may even make 

the public feel safer.

“It’s a nice warm feeling that, for the most 

part, police officers are exactly where they 

need to be, based on what’s anticipated to 

happen that evening,” software director Bill 

Haffey told CBC reporters. 

www.cbc.ca/smartshift/2010/09/fightingcrime-with-data.html

Geography and Public Safety Events

Dealing with crime problems in a local law enforcement agency sometimes 

means reaching out to other local agencies to come up with a solution. 

The events listed here are good opportunities to learn what mapping 

professionals and those in related areas are doing, get new ideas, and 

present your work. 

ESRI Federal User Conference ASPRS 2011 Annual Conference

(FedUC) May 1–5, 2011 

February 2–4, 2011 in Milwaukee, Wisconsin

in Washington, D.C. www.asprs.org/meetings/

www.esri.com/events/feduc/ upmeeting.html

index.html

Jerry Lee Crime Prevention 

National States Geographic Symposium

Information Council (NSGIC) 2011 May 2–3, 2011

Midyear Conference in Washington, D.C.

February 27–March 2, 2011 http://gemini.gmu.edu/cebcp/

in Annapolis, Maryland JerryLee.html

www.nsgic.org/events/future.cfm Society for Prevention Research 

Academy of Criminal Justice 19th Annual Meeting

Sciences May 31–June 3, 2011 

March 1–5, 2011 TBD

in Toronto, Ontario, Canada www.wix.com/sprmeeting/2011

www.acjs.org/pubs/167_668_ 

2915.cfm NIJ Conference

July 20–22, 2011 

Society for Applied Anthropology in Arlington, Virginia

(SfAA) www.ojp.usdoj.gov/nij/events/

March 29–April 2, 2011 welcome.htm

in Seattle, Washington

www.sfaa.net/sfaa2011.html ESRI International User Conference

July 11–15, 2011 

Association of American in San Diego, California

Geographers (AAG) Annual Meeting www.esri.com/events/index.html

April 12–16, 2011 

in Seattle, Washington 118th Annual International 

www.aag.org/cs/annualmeeting/ Association of Chiefs of Police 

register_to_attend (IACP) Conference and Exposition

October 22–26, 2011 

GIS in Action—2011 in Denver, Colorado

March 29–30, 2011 www.theiacp.org/Conferences/

in Portland, Oregon tabid/69/Default.aspx

www.orurisa.org/Events?eventId=208

635&EventViewMode=EventDetails

The Eleventh Crime Mapping 

Research Conference

April 11–15, 2011 

in Miami, Florida

www.ojp.usdoj.gov/nij/events/

welcome.htm
U.S. Department of Justice

Office of Community Oriented Policing Services

Two Constitution Square

145 N Street, N.E.

Washington, DC 20530

To obtain details on COPS programs, call the 

COPS Office Response Center at 800.421.6770

Visit COPS Online at www.cops.usdoj.gov

COPS Editorial Staff MAPS Editorial Staff 

Nicole Scalisi Ron Wilson

Social Science Analyst Program Manager/Social Science Analyst 

Office of Community Oriented Policing Services National Institute of Justice

Marian Haggard Timothy Brown

Editor Research Associate (Contractor)

Office of Community Oriented Policing Services National Institute of Justice

Sandra Sharpe Ariel Whitworth

Graphic Designer Communications Editor

Office of Community Oriented Policing Services National Criminal Justice Reference Service

Visit NIJ Online at www.ojp.usdoj.gov/nij

The opinions, findings, conclusions, or recommendations contained in this publication are those of 

the authors and do not necessarily represent the official position or policies of the U.S. Department of 

Justice. References to specific agencies, companies, products, or services should not be considered 

an endorsement by the authors or the U.S. Department of Justice. Rather, the references are 

illustrations to supplement discussion of the issues.

G&PS readers: 

You may have noticed that although the Geography & Public Safety newsletter is a quarterly publication, the COPS 

Office and NIJ had a delay in publishing Volume 2, Issue 4 due to a transition in management and production roles. 

However, the COPS Office and NIJ remain committed to producing this quarterly newsletter, and you can expect to 

see the next edition in July 2011. If you would like to be featured as an author or highlight your agency’s GIS efforts, 

please contact John Markovic at john.markovic@usdoj.gov or Nicole Scalisi at nicole.scalisi@usdoj.gov. 

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