Thursday, March 21, 2013

Summary of Findings (White Team): Crime Mapping Analysis (3.5 out of 5 Stars)

Note: This post represents the synthesis of the thoughts, procedures and experiences of others as represented in the 8 articles read in advance (see previous posts) and the discussion among the students and instructor during the Advanced Analytic Techniques class at Mercyhurst College in March 2013 regarding Crime Mapping Analysis specifically. This technique was evaluated based on its overall validity, simplicity, flexibility and its ability to effectively use unstructured data.

Description:

Crime mapping is a method that can be used to provide a visual representation of the crime trends and patterns within a jurisdiction. Crime mapping has the ability to increase the capability of the user to identify the “hotspots” or areas within the city with the highest prevalence of crime. Additionally, crime mapping has the ability to provide directionality to where crime may be migrating within the jurisdiction, allowing for an increased amount of resources by law enforcement agencies to be allocated in these areas.



Strengths:

1. Provides visualization of crime trends, patterns, and series.
2. Aids with the practice of intelligence-led policing.
3. Analysis will assist decision makers in formulating strategic and tactical decisions to prevent or minimize crime.
4. Provides the ability to demonstrate directionality of crime.

Weaknesses:

1. Only reports crimes reported to police, not victimization accounts.
2. Just mapping crime data does not help with policing efforts if analysis can not occur from that. Effectiveness is highly reliant on the ability of the officer to use the intelligence to be proactive in their policing efforts.
3. Crime mapping can be prone to confirmation bias.
4. Can be prone to communication problems with decision-makers of what the data conveys.
5. The map can be difficult to interpret if crime locations are overlapping.


Step by Step Action: (Crime Mapping in General)

1. Determine the area of analysis so data can be gathered to create crime maps.
2. Choose crimes that are the most urgent to analyze according to the law enforcement agencies’ needs.
3. Look for hotspots or potential areas of clustered criminal activity.
4. Analyze past crime maps of the jurisdiction to determine if hot spot areas have remained the same for certain crimes, or have migrated to a different area of the jurisdiction.


Exercise:

As a class we went onto crimereports.com to get the crime data for Philadelphia, PA. Each member of the class was given a map of the districts of the city of Philadelphia. Furthermore, each member of the class was given crimes to look up on crimereports.com and determine where the largest amount or most highly clustered of these crimes occurred. Next, we determined what district these crimes occurred most frequently. The culmination of these events allowed the class a basic visualization of where the more crime prone areas of Philadelphia are located based on the crime chosen to analyze.

Summary of Findings (Green Team): Crime Mapping (4 out of 5 Stars)


CRIME MAPPING
Green Team
Rating (4 out of 5 Stars)

Note: This post represents the synthesis of the thoughts, procedures and experiences of others as represented in the 8 articles read in advance (see previous posts) and the discussion among the students and instructor during the Advanced Analytic Techniques class at Mercyhurst University in March 2013 regarding Crime Mapping specifically. This technique was evaluated based on its overall validity, simplicity, flexibility and its ability to effectively use unstructured data.

Description:
Crime mapping is a GIS technique that involves mapping of crimes in order to detect patterns that can focus on enforcement and prevention. Crime mapping has evolved with the shift in policing towards a more proactive approach rather than reactive, called intelligence-led policing.    

Strengths:

  • Visual representation of specific crimes in geographic locations
  • Provides a base for the analysis of trends pertaining to specific crimes
  • Allows for visualization of crime over time

Weaknesses:

  • Relies on reported crimes -- not all crimes are reported to the police
  • Does not ease the communication between the analyst and the decision maker
  • May not be useful for rural areas
How-To:

  1. Decide on the area to investigate for crime mapping
  2. Decide what the ultimate goal is of the investigation (ex: find where assaults are most prevalent in New York City)
  3. Locate and plot relevant data applicable to the investigation
  4. Indicate area(s) where the target crime is most concentrated (ex: along a subway line, in a particular district)
  5. Analyze trends with regard to specific crimes and regions relevant to stated goals -- especially in regard to proactive measures

Personal Application of Technique:
The class individually assessed specific crimes in Philadelphia, PA as mapped on crimereports.com in order to identify the top three hotspots for each particular crime. They then compared the hotspot locations with a handout map provided to show the police district boundaries in the city. The class discussed their findings to compare in which districts their hotspots overlapped for the same crime as well as across different crimes. The class identified hotspots for various crimes primarily in Districts 6, 9, 18, 22, 24, and 26, primarily constituting the center and northern portions of the city. The class then discussed factors that may contribute to these hotspots, including the prevalence of subway systems and residential versus commercial areas.

Rating: 4 of 5 stars

For Further Information:

Notes:

  • Directionality is frequently excluded from analysis
  • Humans are inherently poor identifiers of  hotspots

Tuesday, March 19, 2013

Visualizing the Directional Bias in Property Crime Incidents for Five Canadian Municipalities


Summary:
Crime mapping and related research can be divided between analysis of places, distances, and directions.  Authors Richard Frank, Martin A. Andresen, and Patricia L. Brantingham argue that directionality is the most underrepresented of the three crime mapping analysis elements.  Places and distances traveled are sometimes not comprehensive enough for crime patterns or for particular directions crime is more likely to target.  The authors argue that people are directionally biased towards certain locations.  Strong directionality is found when a person travels from the home to other locations, such as entertainment, work, and shopping, all within a 45 degree angle from the home.  Another way to put this is that a person with strong directionality is likely to travel to locations that are closer to one another and then go home, rather than circling around or returning home before completion of these activities.  Directionality is also influenced by frequency of trips to particular locations.

The authors analyzed data from five municipalities in British Columbia, Canada: Coquitlam, Maple Ridge, Surrey (all within the Metro Vancouver area), Prince George (just outside of the Metro Vancouver area), and Nanaimo (on Vancouver Island).  They used two different kinds of analysis: arrows to show the direction from the home to the criminal incident (exclusive of distance) and colored dots to show the direction of the crime (green equates to south, red equates to north, west equates to blue, and east equates to yellow).  The authors argue that this type of crime mapping visualization technique is an improvement on previously used techniques which appeared convoluted. 

The authors found that this technique was largely successful for mapping the directional bias of criminal activity for each of the municipalities.  They found that the directional arrows or colored dots accurately depicted where criminal opportunity was likely to occur (shopping centers and downtown areas).  The authors suggest analyzing strength of directionality for future research to show which areas are more likely to have higher amounts of criminal activity stemming from them.

Critique:
This study does a good job emphasizing the importance of directionality for crime mapping.  It is easily applicable to law enforcement intelligence as a tool to locate origin points in neighborhoods with particularly high quantities of crime emanating from them.  The same idea can be used for other topics such as competitive analysis for product information distribution (ex: examining the magnitude of where people from certain areas like to shop). 

I was somewhat confused how geometry was critical to this analysis as directionality was only shown in one direction instead of the interconnectivity of home, work, entertainment, and shopping.  Additionally, the authors argue the arrows simplify the mapping process.  However, I believe some areas are unreadable due to the quantity of arrows in a particular location.  Lastly, the rainbow dots symbolizing crime direction seem like a good idea at first, but are not easily readable in reality.  I found myself examining the color key on many occasions trying to remember which color symbolized which direction.  This analysis could be improved by changing how the arrows are represented (maybe one big arrow for a higher crime area), remove similar arrows for simplification, or simplifying the colors to four or eight colors for readability. 

Source:
Frank, R., Andresen, M.A., & Brantingham, P.L. (2013). Visualizing the directional bias in property crime incidents for five Canadian municipalities. The Canadian Geographer, 57(1), 31-42. Retrieved from: http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0064.2012.00450.x/pdf

Crime Mapping and the Training Needs of Law Enforcement


Summary:
Ratcliffe's article Crime Mapping and the Training Needs of Law Enforcement identifies three main aspects of crime mapping, or applications of geographic information systems (GIS): hotspot mapping, CompStat and geographic profiling. Techniques in exploratory spatial data analysis (ESDA) can reveal crime patterns and hotspots of criminal activity that are invaluable to law enforcement agencies. Spatio-temporal mapping and geographic profiling using the GIS methodology is an evolving technique with increasing complexity and can offer vital information for intelligence-led policing in crime reduction and prevention. Ratcliffe mentions that although this technique offers a new form of useful intelligence for law enforcement, it does not undermine non-spatial features of crime records such as modus operandi and temporal variables.

The author defines crime mapping as a way to collect, store, analyze and disseminate information relating to the earth. The first application of GIS in law enforcement is hotspot mapping. This is the input and conversion of crime data into spatial features. The following two images are examples of hotspot mapping of vehicle crimes in Philadelphia for July 2002. In the following two images, Image 1 demonstrates how hotspot mapping appears when each individual crime is represented as a dot while Image 2 shows the same image after using kernel density smoothing. Image 2 is less precise but more clearly displays the actual hotspots.

Image 1:

Image 2:


Although GIS is most frequently used to map property and violent crime, it can also geographically represent calls for service, race and other socio-economic data for a more complex analytical map. It is also effective at demonstrating measurable long-term crime prevention and reduction.

The second application of GIS is CompStat, or Computer Statistics. This is a management process that increases accountability and requires commanders to actively analyze crime patterns. As the author states, it requires a quick conversion of crime data to geographic visuals of the data. The third and final application is geographic profiling, an investigative technique that aids in serial crimes and helps to identify potential criminals on a map. The idea was developed from a combination of theories, including the routine activity theory and rational choice theory that suggest that people develop a daily routine and through knowledge of such a routine, police can identify key nodes for offenders in certain locations. This is helpful in suspect prioritization and patrol saturation.

Ratcliffe claims that while GIS is evolving rapidly and is a crucial element to law enforcement intelligence, agencies are not devoting enough time to training their officers and analysts. He believes that while the number of agencies using it is increasing, many still do not understand its importance and application to policing and are sticking to the traditional policing techniques that they are familiar with.

Critique:
Ratcliffe's article effectively demonstrates the important of geographic information systems application in law enforcement. The identification and explanation of three aspects of crime mapping was beneficial and their usefulness in the field was evident. He explicitly mentions that geographic profiling produces a map of risk which demonstrates visually the likelihood of criminal activity, the main purpose of intelligence analysis. Through crime mapping, risk can be reduced for a decision-maker.

The author states many limitations to GIS, however. Hotspot mapping has issues with points that overlap, human inability to define clusters and the difficult of establishing broad trends. Some of these concerns are reduced through additional extensions of GIS programs, but the issue of data overload is nevertheless cumbersome. Additionally, geographic profiling is believed to have limitations for some offender types which may have negative implications for risk reduction. Among these were implicit limitations as well, including GIS's ever-evolving nature which makes it difficult for analysts to continuously learn the updates and for new practitioners to enter the field.

While Ratcliffe's article was useful, he redirected to many outside sources rather than including the information within the actual article which made it seem somewhat incomplete. Elaborating further on the three applications of GIS, offering potential solutions to issues in training and explaining the limitations further would have solidified his argument.

Source:
Ratcliffe, J. H. (2004). Crime mapping and the training needs of law enforcement. European Journal on Criminal Policy and Research, 10(1), 65-83. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.107.2771

The Diffusion of Computerized Crime Mapping in Policing: Linking Research and Practice

Summary:
Authors David Weisburd and Cynthia Lum conducted a research study in the Journal of Police Practice and Research, which examined the relationship between the research and the diffusion of computerized crime mapping in police departments in the United States. Crime mapping allows police departments and officers to see "hot spot" areas where crimes are taking place.  This allows the department to re-evaluate their distribution of resources and address areas which "attract" a certain type of crime at a certain frequency.

For this study police departments with at least 100 sworn officers were chosen random, to result in 125 police agencies.  Within each of these departments, individuals were contacted to determine if the department had computerized crime mapping capabilities, when it was implemented and the manner in which is was used.  To evaluate the use of computerized crime mapping, the researchers sent a survey to the randomly chosen agencies from September to November of 2001.  The purpose of this research was not only to determine if they use computerized crime mapping, but also the exact year they adopted it.

The authors determined that diffusion of computer crime mapping was seen after 1997 and a majority of the departments had adopted the mapping system by 2001. While there was an increase in technology, the authors argue that it was not sufficient enough to cause the widespread adoption of the technique.  Therefore, they propose that the combination of technological advances coupled with a change in the manner of policing led to the dissemination of computerized crime mapping.

Critique:
This study provided an interesting analysis relating to the use of computerized crime mapping.  Though, a majority of the published article focused on the history of policing, specifically in the 1970's and 1980's.  During this time there was a change in the approach of policing, which eventually led to crime mapping.  While this study does not explicitly link the intelligence field, it provides a relevant insight into the analysis of crime. The change in the approach to policing allowed for the development of computerized crime mapping.  The analytic application of this method is applicable to the intelligence field and can be used not only for crimes, but also to map key areas where specific events are taking place.

Weisburd, D. & Lum, C. (2005). The diffusion of computerized crime mapping in policing: Linking research and practice. Police Practice and Research, 6(5), 419-34. Retrieved from http://ehis.ebscohost.com/eds/pdfviewer/pdfviewer?vid=4&sid=45180a6c-1beb-4f54-97d9-dc1ae165ccf1%40sessionmgr13&hid=6 

Crossing the Borders of Crime: Factors Influencing the Utility and Practicality of Interjurisdictional Crime Mapping

Introduction:
John Eck's article Crossing the Borders of Crime: Factors Influencing the Utility and Practicality of Interjurisdictional Crime Mapping provides a look into five different categories of factors that influence the utility of crime mapping, particularly Cross Boundary Crime Mapping Systems (CBCMS). These categories are action, patterns, data, administration, and access, and are listed in descending importance according to the author (Eck 2002, p.3). The article reviews factors that affect the utility of inter-jurisdictional crime mapping specifically but many of these factors affect the utility of crime mapping as a methodology in general.

Summary: 
Crime mapping has grown as a methodology employed by a large number of law enforcement agencies especially as technology has developed further to increase capabilities while lowering expense. Like all methodologies, crime mapping relies on certain factors to be useful. Eck identifies five categories and the specific factors involved that determine the utility of crime mapping, particularly in terms of CBCMS. The first category, action, asks what will agencies use the information from the CBCMS for and will they take action to address the crime patterns they discover? Crime mapping and particularly CBCMS are of little utility if agencies never act on the results, which Eck (2002) points is all too common (p.4).

The patterns category identified by Eck is most applicable to CBCMS, with little influence on the utility of crime mapping in general because patterns fall into the categories of no pattern, no shared pattern, shared patterns, shared boundary problems, barrier borders, attracting borders, pseudo barriers, and common problems. While no patterns would prove crime mapping in any case rather useless, the pattern or lack thereof can only be determined after crime mapping is performed.

Data, on the other hand, has many factors that affect the utility of crime mapping in any situation, given that any methodology will fail if data is inaccurate or irrelevant. Data used in crime mapping must include information describing specific locations, incident types, and dates of occurrence (Eck 2002, p.2). This data is affected by citizens reporting, agency recording, event classification, descriptive information, and geocoding. Almost all of these can be attributed to human error.

The final two categories, administration and data dissemination, are closely related and rely on who decides how and when information is shared. While this seems most applicable to CBCMS, who governs crime mapping within a single agency will still affect its utility and application.

Critique:
While Eck's article falls lower on the Pyramid of Evidence (refer to Source and Methods), his article is important in understand the utility of crime mapping as a methodology, particularly in the law enforcement intelligence field. As stated before, while his intent was to identify those factors affecting the utility of CBCMS, factors such as data accuracy and action taken upon results certainly affect the value of crime mapping more generally. The article would be strengthened with case study or experimental results, however, the jurisdictional mapping examples provided strengthen the patterns sections significantly.

In terms of the methodology itself, crime mapping is heavily reliant on analysts avoiding common human errors, some of which are not within their control. For instance, a crime analyst cannot easily affect the frequency that citizens report crimes. Additionally, crime maps that only include arrest data as opposed to incident data will be greatly skewed to where agencies have the most manpower, not necessarily the areas with the most crime. Aside from data, crime mapping, like many other methodologies, suffers when its results go unused. If crime mapping is performed strictly to identify locations of past crimes without anyone using the results to predict future crime or other methods of addressing the underlying problem, the methodology is of little utility in the intelligence field.

Source:
Eck, J. (2002, January). Crossing the Borders of Crime: Factors Influencing the Utility and Practicality of Interjurisdictional Crime Mapping. Overcoming the Barriers: Crime mapping in the 21st Century. Retrieved from http://www.policefoundation.org/sites/pftest1.drupalgardens.com/files/Eck%20(2002)%20-%20Crossing%20the%20Borders%20of%20Crime.pdf 


Crime Mapping and the Crimestat Program

Summary:

The article Crime Mapping and the Crimestat Program begins with an overview of the Crimestate program and its contribution to crime mapping.  The Crimestat program provides supplemental statistical tools to aid law enforcement agencies and criminal justice researchers in crime mapping.  It specifically highlights version 3.0 and emphasizes its ability for law enforcement personnel to analyze travel patterns over metropolitan areas.  It is designed to increase the effectiveness of crime mapping and other GIS applications as well as work with large databases considering most police department work with large files. 


Following a brief overview of Crimestat the article provides a detailed definition of crime mapping.  It states that crime mapping is the mapping of crime incidents in order to detect general patterns of crime to better allocate resources for enforcement and prevention as well as to identify and apprehend offenders committing crimes.  It has multiple uses, examples include, planning efficient deployment strategies to focus on hot spots, tracking the behavior of serial offenders, and mapping motor vehicle crash locations.

The article provides detail into the statistics built into the program to make crime mapping more efficient and easier to use.  First, the author describes spatial statistics.  He states that a key concept in spatial statistics is spatial autocorrelation, defining it as events that are spatially arranged in a nonrandom manner, either more concentrated or, occasionally, more dispersed than would be expected on the basis of chance.  Next, the author provides a description of hot spot analysis, an extreme form of spatial autocorrelation, stating that incidents, mainly criminal activities are concentrated in a limited number of locations.  Spatial modeling is the next area of focus.  The first method in this category is interpolation, the act of extrapolating a density estimate from individual data points.  It involves the placement of a fine-mesh grid over the area under study and the distance from each grid cell to each data point in calculated.  This is followed by an estimate of incident density for each grid cell.   Journey-to-crime analysis is the next analytical tool discussed and is a criminal justice method for estimating the likely residence location of a serial offender when given the distribution of incidents and a model for travel distance.  Space-time analysis precedes journey-to crime-analysis and includes many routines for analyzing clustering in time and space including the Knox and Mantel indices as well as the Correlated Walk Analysis module.  The final statistical tool is crime travel demand that models criminal travel behavior over a metropolitan area.  Finally, the article is comprised of a section discussing the miscellaneous options in Crimestat. The concluding paragraphs reemphasize the importance of GIS and crime mapping overall into law enforcement.  Furthermore, the author reiterates the need for statistical tools to aid in the assessment of the important trends in the data.

Critique:

CrimeStat, a statistical tool used to increase the usefulness of crime mapping is likely to increase the effectiveness of crime mapping overall but considering the program developer is the writer of the article it has the potential to be biased.  It would have been useful to include reviews or opinions by its users in the law enforcement field or other users such as students, professors, researchers or analysts to minimize the possibly of bias.  

The article states that CrimeStat is one of the many tools developed to summarize and assess the trends in crime mapping.   Examples of other tools used to achieve the same results for comparison reasons would provide the reader with a better means to assess Crimestat's effectiveness over other programs.
Given the nature of the article, to incorporate and explain Crimestat and its use in crime mapping, a more through explanation of the relationship between the different types of crime mapping and Crimestat’s contribution to these methods would be highly useful.  For example, Crimestat provides seven hot spot analysis routines including the mode, the fuzzy mode, hierarchical nearest neighbor clustering, risk adjusted nearest neighbor hierarchical clustering, the Spatial and Temporal Analysis of Crime routine, and K-means clustering.  An example giving a basic overview of each of these analysis routines would provide a better understanding of Crimestat's functions in relation to crime mapping while allowing the reader to compare and contrast the methods evaluating what method is most effective in a particular situation.   Furthermore, Crimestat uses five different mathematical functions to estimate the density and has two different applications including  a single-variable density estimation and a dual-variable density estimation routine.  Again, the author mentions Crimestat  and the five different mathematical functions as well as the two different applications the program is able to use.  This is another instance in which more examples would prove to be effective in understanding the functions and their contributions to crime mapping.  This would allow for  an overall better understanding of the program and crime mapping in general.  

The article discusses Version 3.0 of Crimestat stating it has a crime travel demand module of modeling criminal travel behavior over an entire metropolitan area.   The author focuses on the concept of aiding law enforcement in metropolitan areas throughout the article.  While this is useful, it is also important to emphasize on its effectiveness in smaller law enforcement agencies.  In the conclusion, the author stresses the strong need for statistical and other analytical tools that can summarize the trends in the data.  Although visuals and graphs are provided for some methods, specific examples for each method and an outright description as to how it relates to crime mapping would be beneficial. This would allow for  an overall better understanding of the program and crime mapping in general.   

Source:

Levine, Ned. (2004). Crime Mapping and the Crimestat Program. Ned Levine & Associates, 41-56. Retrived from http://cs.iupui.edu/~tuceryan/pdf-repository/levine2006crime.pdf 

Monday, March 18, 2013

The History of Crime Mapping and Its Use by American Police Departments

Summary:

     In an article published in 2006 in the Alaska Justice Forum, Sharon Chamard discusses the history of crime mapping, the advantages and disadvantages of computerized crime mapping, and the decreasing number of police departments that are conducting crime mapping analysis.

     Crime mapping can trace its origins back to 1829 France, when Adriano Balbi and Andre Michel Guerry created maps that showed the relationship between education levels and violent crimes. By the mid-19th century that practice had made its way over to England and Wales, where the techniques was applied to other types of crimes. In the early 1900s, the University of Chicago started using the technique for various studies. The maps that were produced could be 70 feet in length and take many hours in meticulous work to color in areas or put thousands of dots representing points of interest. Crime mapping was not widely adopted until the late 1980s, when desktop computers became widely available to police departments.
     While computers have made the use of crime mapping easier and more widely adopted, there are still issues with it. Chamard cites the learning curve of mapping software, specifically ArcView and MapInfo as an issue, especially in departments that have a relatively low number of personnel. There are also issues of integrating crime mapping into the normal department routine. A third issue is that the majority of departments using the technology for crime mapping end up using the software to create pin maps and hot spot maps, both of which are at the low end of analysis. Analysis above these levels requires some knowledge of cartography and GIS, which the majority of police departments lack.
     The last issue Chamard examines is why a large number of departments stop using this technique. A study  by Chamard from 1997 to 1999 found that of 615 departments that reported using crime mapping, 242 had stopped using it by 1999. The study found that department size was the best predictor of discontinuance. Departments with less than 250 sworn officers were much more likely to discontinue crime mapping than departments with more than 250. Issues with crime mapping that were specifically stated ranged from software issues, issues obtaining current maps, and a lack of benefit using the technique.

Critique:

     The most noticeable issue with Charmden's paper is that it does not go into detail on the utility of the technique. She cites issues that departments have had in implementing crime mapping with computers, which is almost a moot point considering the alternative of utilizing the technique without computers. She also discusses interesting studies showing that a large number of departments that have used crime mapping in the past have stopped. She lists various reasons why this is happening, but she never once goes into the effectiveness of the technique. Granted that this paper is not aimed at explaining the merits of crime mapping, but it would have been helpful, especially since she hints at its use if properly used.    
     Charmden's studies of why departments have stopped utilizing the technique present two problems with crime mapping. The first is that the benefits of the technique do not seem to be fully known. This can be attributed to the learning curve of the software and the technical expertise that most departments lack. Departments with more personnel have larger budgets, meaning of they do not directly hire someone with the expertise to use the software, they can at least afford to send interested personnel to classes, giving them the technical expertise. This would also allow deeper analysis past the pin maps and hot spot maps that are commonly created. By effectively utilizing deeper analysis, the ability for crime maps to eliminate uncertainty would increase, demonstrating their usefulness.
     The second issue with crime mapping is that it might not be applicable to all departments. While the technique can be applied to cities, the same might not be said for suburban and rural areas. These areas are normally larger, with more spread out crime. These departments are also typically smaller than city departments, meaning that their resources are more limited. With more limited resources and a less centralized area, crime mapping might not be as useful or needed as with urban departments.

Charmden, S. (2006). The History of Crime Mapping and Its Use by American Police Departments. Alaska Justice Forum, 23(4), 4-8, Retrieved from http://justice.uaa.alaska.edu/forum/23/3fall2006/a_crimemapping.html                       

Sunday, March 17, 2013

To Map Or Not To Map: Assessing The Impact Of Crime Maps On Police Officer Perceptions Of Crime


To Map Or Not To Map: Assessing The Impact Of Crime Maps On Police Officer Perceptions Of Crime


Summary:

            Geographic Information Systems (GIS) technology allows the user to utilize computer-mapping systems to spatially analyze data such as crime incidents (Paulsen, 2004).  The purpose of this software is to spatially analyze information from crime incidents in order for policing efforts to put more resources towards higher at risk areas within their jurisdictions.   Law enforcement highly values crime-mapping technology to conduct intelligence-led policing.  Intelligence-led policing gives law enforcement the ability to act more proactively towards criminal activity.  However, to perform intelligence-led policing requires the law enforcement agency to have an accurate understanding of the crime patterns in their jurisdictions and ability to understand what the crime maps inform the officers about hotspots in their jurisdiction (Paulsen, 2004).  Paulsen (2004) conducted an experiment to evaluate the effects of crime maps on officers’ perceptions of crime patterns and how it affected their patrol activities to perform intelligence- led policing.
                To collect data for the experiment Paulsen (2004) utilized a police department from a post of the Kentucky State Police.  The post of the Kentucky State Police agreed to be apart of the researcher’s program called Tactical Mapping and Analysis Program (TMAP), which provided both police executives and patrol officers with up to date crime maps on crime incidents in their jurisdictions.  The goal was for both groups to use the data provided by the crime maps to lead intelligence-led policing efforts to develop proper strategies in which to target current and emerging crime problems.  Crime maps were able to give daily, weekly, and monthly maps with no lag time for officers of the Kentucky State Police (Paulsen, 2004).    
            To determine police perception of crime and if crime maps influenced their intelligence-led policing efforts Paulsen (2004) used a test and control group, along with pre-test and post-test experimental measures.  Prior to beginning TMAP, the 40 officers in the Kentucky Police Department were split into a test and control group and asked pre-test questions that dealt with their background, sources of main crime information, and perceptions of crime patterns within their jurisdictions (Paulsen, 2004).  Additionally, the officers were given a map of their jurisdiction and were asked to label the five most crime ridden areas.  Officers from the test group received daily, monthly, and weekly crime maps for two months.  After two months Paulsen (2004) analyzed if there were any changes to the spatial perceptions of crime by each group of officers with the use of crime maps over a two-month duration.
            The analysis of the experiment expressed that police officers do not have a good understanding of crime patterns within their respected their jurisdictions, with most only able to identify two of the top five highest crime areas in their jurisdiction (Paulsen, 2004).   As compared to the control group who didn’t receive crime maps, those officers who did receive crime maps proved no more accurate than those officers who were not given crime maps over the duration of the two month study to identify the highest area of crime within their jurisdictions (Paulsen, 2004).    

Critique:

            The study conducted by Paulsen (2004) expressed that intelligence-led policing efforts that utilize the information displayed with crime mapping software does very little to guide intelligence efforts to shape jurisdiction policing strategies if officers are not educated on how to properly use these sources.  Just giving officers crime maps does not give them the analytical skills necessary to interpret what is presented in the crime maps and apply it to intelligence-led policing efforts.  Furthermore, the study suggests that the culture surrounding police officers’ perception of where high-risk crime areas are located is highly engrained in the studied patrol officers’ daily experiences of patrolling and officers demonstrated an unwillingness to acknowledge what the analyzed data of crime maps conveys.  Moreover, it is necessary that police officers are educated on the proper analytical techniques to understand crime maps.  For intelligence-led policing to be effective it must go beyond the officers perceptions of what the real threat is in their jurisdictions and a proper analysis of crime maps will allow officers to be more successful in their intelligence gathering and policing efforts.
            However, even though the study conducted by Paulsen (2004) expressed important implications of the use of crime mapping among patrolling officers and its effect on the successfulness of intelligence-led policing, the results should be taken with some speculation.  The police agency that was used as a sample for this study was mostly in a rural area of Kentucky.  A future study would be needed to determine if crime mapping practices are different in urban areas and if police perceptions of where high crime areas are incorrect in urban areas as well.   Moreover, a larger sample size and pulling officers from different areas of the country would be needed to provide increased support for the outcome of the experiment.  Predominantly, the states in the south of the United States have higher crime rates so it would be interesting to conduct this experiment comparing law enforcement in northern and southern states and their perceptions of where the hotspots of crime are in their respected jurisdictions. 
            Lastly, it is important to affirm that this study did not avow police officers were less effective with their current understanding and utilization of crime maps, or that with crime maps intelligence-led policing increased the effectiveness of the police agency.  However, in terms of the benefits of intelligence-led policing the study delved into the possibility that it is a much-needed intelligence gathering strategy for law enforcement agencies to implement to be able to combat not just current crime issues, but emerging risks in their jurisdictions.  Properly analyzing trends will allow law enforcement agencies with the ability to make crime analysis that is future orientated, the main goal of intelligence gathering allowing for a reduction of uncertainty for law enforcement decision-makers.    

Source:

Paulsen, Derek J. (2004). To Map Or Not To Map: Assessing The Impact Of Crime Maps On Police Officer Perceptions of Crime. International Journal of Police Science & Management, 6(4), 234-246.  Retrieved from http://ehis.ebscohost.com/ehost/detail?sid=75d3db08-d830-49d4-831c-47050e61df7b%40sessionmgr10&vid=1&hid=3&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=a9h&AN=15073048