GIS and Evidence-Based Policy Making - Chapter 6

6 Crime Map Analyst: A GIS to Support Local-Area Crime Reduction Paul Brindley, Max Craglia, Robert P. Haining, and Young-Hoon Kim CONTENTS 6.1 Introduction............................................................................................... 113 6.2 Current Crime Pattern Analysis............................................................. 115 6.2.1 GIS Crime Systems in the United States................................... 115 6.2.2 Past Crime Mapping and Analysis Research......................................................................... 115 6.2.3 Background to Crime Map Analyst........................................... 118 6.3 Overview of Crime Map Analyst........................................................... 118 6.3.1 Density Maps................................................................................. 119 6.3.2 Repeat Victimization Identification........................................... 121 6.3.3 Temporal Analysis........................................................................ 122 6.3.4 Area Profiles.................................................................................. 124 6.3.5 Origin=Destination Analysis....................................................... 125 6.3.6 Ancillary Tools.............................................................................. 126 6.4 Conclusions................................................................................................ 127 Acknowledgments............................................................................................. 129 References ........................................................................................................... 129 6.1 Introduction The importance of geographical information systems (GIS) for crime analy-sis, and strategic and tactical deployment of forces, has been increasingly recognized in both the United States and the United Kingdom. This was forcefully endorsed by former New York mayor, Rudolph Giuliani, during his visit to London in February 2002. 2007 by Taylor & Francis Group, LLC. Senior police officers are keen to learn from the New York experience while Mr Giuliani visits London. In the eight years he was mayor of New York crime plunged. The success was credited to CompStat, the computerised system which keeps track of week-by-week crime figures for each precinct, the basic division of the city’s police department. (The Guardian, 14th February 2002) CompStat is of course only part of a wider strategy of crime reduction, but it makes the point that the regular analysis of crime for small geographical areas is crucial for the effective deployment of resources, monitoring and evaluating impacts, and sharing intelligence. The increased emphasis by the Home Secretary on increasing detection rates by concentrating police resources into selected hot spot areas goes in the same direction. The ability to visualize and analyze the data geographically is at the heart of GIS. These types of systems are already widely used in the United Kingdom, but there are significant variations among the forces in extent and purpose of use (Weir and Bangs, 2007). There are therefore opportun-ities for using GIS more and better, with stronger integration to crime-reduction strategies both in the forces themselves and as part of the wider crime-and-disorder partnerships. GIS can add value to the data already held by police forces and become a more integrated tool in crime-reduction strategies. There are two essential preconditions to make this happen. 1. Geo-coded data GIS can only operate effectively if the data to be analyzed have accurate and consistent geographical locations attached to it. Although this may sound a purely technical matter, it is in fact a largely organizational one. It must become a routine to report the location of crime events as accurately as possible, and against a standard gazetteer of locations. Not all forces have adopted such practice and the assigning of coordinates to past crime data pro-vides context to the analysis. 2. Awareness and training Training staff in the use of GIS, or any new system, is of course time consuming and expensive. The advantage however of adopt-ing off-the-shelf and widely used software is that there are already well-developed courses, training packages, and learning resources, and that there is a support network of millions of users on which to build. This minimizes training costs and makes the most effective use of the investment made. Perhaps, more crucial is ensuring that the necessary awareness exists among senior managers of the value of such investment, and that adequate support is provided. 2007 by Taylor & Francis Group, LLC. 6.2 Current Crime Pattern Analysis 6.2.1 GIS Crime Syste ms in the United States The importan ce given in the United Stat es to GIS for crime analys is is clearl y demo nstrated by the work of the Map ping & Analy sis for P Safet y (MAP S) program (formerly the Crim e Mapp ing Rese arch Center) the Nationa l Institute of Justi ce==w(hwttpw: .ojp. usdoj.go=nvij=maps ). This center was established in 1997 to promote, research, evaluate, develop, and disseminate GIS technology and the spatial analysis of crime. The lessons learned out of the U.S. situation are valuable in the continued development of crime mapping in the United Kingdom. Personal contact using the CRIMEMAP e-mailing group (crimemap@lists. aspensys.com) was undertaken to disseminate crime mapping and analysis e-mails to all subscribers to discover the main GIS used within U.S. crime mapping. The survey was conducted during 11–31 October 2000, and a total of 93 contacts were collected. Findings support other crime-mapping sur-veys by several governmental crime-research agencies (Crime Mapping Research Center, 1999; Police Foundation Crime Mapping Laboratory, 2000), whereby over 50% of crime analysis and mapping in the United States was undertaken using just two software applications—ArcView and MapInfo. 6.2.2 Past Crime Mapping and Analysis Research Since the 1990s, the extensive usage of GIS has enabled police forces to map and analyze crime data efficiently, facilitating crime data analysis (Hirschfield et al., 1995). Computerized mapping technology has broad application areas in various police fields including operational, analytical, and strategic policing (Craglia et al., 2000). GIS functionality has become widely used in many areas within crime data analysis, such as crime hot spot mapping and cluster detection, repeat victimization, temporal pattern analysis of crime incidents, and police pol-icy making for crime reduction and prevention. For hot spot analysis, Ratcliffe and McCullagh (1999) developed a methodology for detecting various hot spots using a kernel estimate function on the basis of a local spatial autocorrelation statistic (Local Indicators of Spatial Association, LISA) to identify statistical hot spot variation. Crime cluster detection has been carried out within several current crime mapping tools such as STAC and CrimeStat (Bowers and Hirschfield, 1999; Levine, 1999; Craglia et al., 2000). Farrell and Pease (1993) recognized the issue of repeat victimization as a main criminological problem and suggested an implementation strat-egy for preventing crime repeats. Anderson et al. (1995) also provided strategic guidance for police forces to tackle repeat victimization. Johnson et al. (1997) demonstrated the relationship between repeat victimization 2007 by Taylor & Francis Group, LLC. and other soc ioeconom ic factors, and exp lored analyti cal me thods iden tify the re lationship . Howeve r, geo-co ding pro blems have a profou impa ct upon the reliabi lity of spat ial repeat vic timizatio n iden tificat (Ratcli ffe and McCu llagh, 1998a) . The tempo ral as pect has been iden tified as a crucial factor to mo n crime incide nt change. Instea d of using general discrete methods (for examp le, usin g mi d-point of bet ween from -time and to-time interva Ratcl iffe and McCu llagh (1998b) introdu ced a prob abilistic rate techn iq bas ed on aori stic rul es to estim ate a truer rate of crime incide nts. A desc ription of this method ology will be discusse d in Secti on 6.3.3 . Prac use of this method was und ertaken to explor e differen t tempo ral pattern crimes with in a nu mber of ho tpots (Ratcliffe , 2002). Spa tial st atistics been increasi ngly appli ed to crime data analys is in ord er to enhan ce capa bilities of GIS-bas ed analy sis of crime, suc h as local spatial statis for crime pat tern a nalysis (Craglia et al., 2000), urban crime exami natio (Mur ray et al., 2001), or det ecting tempo ral chang es of crime (Ro gerson Sun, 2001). Anselin et al. (2000) introduced the extensive discussi on of spat ial analytical techni ques and poten tial of GIS for crime analysi s. add ition, for exp loring the relations hip with socioeco nomic area pro f and crime incide nts, Bowe rs and Hirsch field (1999) demo nstrated a examp le of GIS applicati ons in crime pat tern analy sis, a nd Craglia e (2001) re ported the strengt hs of GIS -based spatia l analysi s with censu s for mo deling hi gh-intensi ty urb an crime areas. Hirsch field and Bowe (2001) sum marized extensive research contr ibutions of GIS and their prac-tical poten tial in crime data mapp ing and analy sis. A varie ty of crime mapp ing syst ems, extensio ns, and softwa re pac k for GIS have been develo ped at practica l level s, as summar ized Tab le 6.1. Some packag es were develop ed for pin pointin g crime eve and creating thematic choropleth maps, whereas other software systems were developed for locating hot spots and exploring spatial relationship with other socioeconomic data. For example, STAC was a frontier stand-alone hot spot and cluster analysis package developed in the 1980s and still is useful for crime cluster analysis (Craglia et al., 2000). In the 1990s, many mapping packages have been developed as extensions of main GIS commercial software systems using their customization languages such as SCAS, CrimeView and Crime Analysis for ArcView, and Hotspot Detective for MapInfo. To improve their user interface, computer lan-guages and scripts have been integrated such as Visual Basic (SCAS, RCAGIS, and CrimeStat), and MapObject (RCAGIS and Community Policing Beating Book, and MaxResponder). As an alternative, crime-oriented stand-alone mapping software has been developed such as PROphecy and CrimeWatch. However, there has been limited success to tackle crime data analysis for various levels of U.K. police force require-ments. Therefore, this chapter demonstrates some of the key functions of GIS crime analysis that can meet various operational, tactic, and strategic police performance in the U.K. police force. 2007 by Taylor & Francis Group, LLC. TABLE 6.1 Summary of Main Available Crime Mapping Desktop Software Name Source Primary Functionality Spatial and Illinois Criminal Justices, 1993 (h==ttp: Hot spot analysis package Temporal www.icjia.state.il.us=public=index. Analysis of Crime cfm?metaSection¼Data&meta (STAC) Spatial Crime Analysis System (SCAS) Regional Crime Analysis GIS (RCAGIS) Community Policing Beating Book Crime Analysis Extension CrimeView Page¼STACfacts, assessed 18th October 2007) CMRC, 1994 (htt=p=w: ww.usdoj. gov=criminal, assessed 18th October 2007). CMRC, 1994 (htt=p=w: ww.usdoj. gov=criminal, assessed 18th October 2007). ESRI, 1997 (htt=p=w: ww.esri. com=industries= lawenforce=beatbook.html, accessed on 6th June, 2002) ESRI, 1999 (htt=p=w: ww.esri. com=industries=lawenforce= crime_analysis.html, accessed on 6th June, 2002) OMEGA, 1999 (h=t=tpw:ww. theomegagroup.com=crimeview. Query interface; analytical mapping and reporting; installation flexibility; minimum reprogramming (avenue) Low cost<($100); analytical mapping and reporting; interface with CrimeStat and MapObject Simple query; mapping and reporting functions; MapObject application ArcView application using Spatial Analyst extension; Hot spot and cluster analysis Query; density mapping and simple analysis; reporting; htm, accessed on 6th June, 2002) integrated with ArcView MaxResponder Hot spot Detective Repeat Location Finder ReCAP-SDE CrimeWatch ESRI, 1999 (h=t=tpw:ww. maxresponder.com=, accessed on 6th June 2002) Ratcliffe, 1999 =(=hattthpe:ne.csu.edu. au=jratclif=index.html, accessed on 6th June, 2002) Ratcliffe, 1999 (htt=p=a: thene.csu.edu. au=jratclif=index.html, accessed on 6th June, 2002) Virginia Institute for Justice Information, 2000 (htt=p=v: ijis.sys. virginia.edu=home.htm, accessed on 6th June, 2002) Spatial Data Inc., 2000 =(=hwttwp:w. spatial-data.com=pCrimeWatch. Query and mapping function; mobile GIS mapping functions Hot spots; aoristic temporal analysis Spatial repeat victimization identification A stand-alone package; data handling and chart reporting functions Database; geo-coding and reporting functions htm, accessed on 6th June, 2002) CrimeStat Levine, 2000 (h=t=tpw:ww.icpsr. umich.edu=NACJD=crimestat. Well-suited stand-alone software; set of spatial html, accessed on 6th June, 2002) statistical modules for crime analysis; hot spot and clustering functions; compatible of main GIS software packages PROphecy ABM, 2000 (h=t=tpw:ww.abm-uk. Hot spots; temporal analysis com=uk=index.asp, accessed on 6th June, 2002) 2007 by Taylor & Francis Group, LLC. ... - tailieumienphi.vn