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GIS APPLICATIONS IN CRIMINAL JUSTICE

GIS APPLICATIONS IN CRIMINAL JUSTICE. Melanie Tennant, Research Associate Gisela Bichler-Robertson, Director CPAL-CSU, San Bernardino Association for Criminal Justice Research Oct. 18-19, 2001, San Diego http://cjrc.csusb.edu/CPAL/CPAL.html. I. What is GIS?.

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GIS APPLICATIONS IN CRIMINAL JUSTICE

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  1. GIS APPLICATIONS IN CRIMINAL JUSTICE Melanie Tennant, Research Associate Gisela Bichler-Robertson, Director CPAL-CSU, San Bernardino Association for Criminal Justice Research Oct. 18-19, 2001, San Diego http://cjrc.csusb.edu/CPAL/CPAL.html

  2. I. What is GIS? Geographic spatial realities Information data and their meaning System computer technology CPAL- CSU San Bernardino

  3. The GIS Funnel Source: Davis, B., (1996). GIS a Visual Approach. Onward Press. Pg. 26. CPAL- CSU San Bernardino

  4. GIS Analysis: Techniques using maps to explore data and identify patterns. • Pin Maps • Cloropleth or Thematic Maps • Density Maps CPAL- CSU San Bernardino

  5. Current GIS Applications inCriminal Justice • Law Enforcement • Arson Investigation • Border Patrol • Police Departments • Courts • Corrections • Probation/Parole CPAL- CSU San Bernardino

  6. II. Police Use of GIS • Augment Traditional Functions • Crime Analysis • Information Dissemination • Enhance Problem Solving • Community and Problem-oriented Policing • Task Forces CPAL- CSU San Bernardino

  7. Enhancing Traditional Crime Analysis Strategic • Identify unusual activity levels by time or location • Forecast potential crime events/ concentration CPAL- CSU San Bernardino

  8. Source: Bueermann, J. (1999). Mapping for Managers. CMRC 10th Annual Conference. CPAL- CSU San Bernardino

  9. Tactical • Day to day • For series, patterns, sprees, hot spots • Used for Deployment & Administration CPAL- CSU San Bernardino

  10. Source: Bueermann, J. (1999). Mapping for Managers. CMRC 10th Annual Conference. CPAL- CSU San Bernardino

  11. Investigative • crime scene, psychological & forensic information • link serial or related events • Temporal, geographic, DAN evidence to develop trends CPAL- CSU San Bernardino

  12. CPAL- CSU San Bernardino Source: Rossmo, 1999. Figure 6.1. In: K. Harries. Mapping Crime:Principle and Practice. NIJ.P.153

  13. Intelligence • linkage between crime organizations & enterprises • Relate elements such as companies, agencies, people, times, days, to crimes & places CPAL- CSU San Bernardino

  14. CPAL- CSU San Bernardino

  15. CPAL- CSU San Bernardino

  16. Operations • Assess needs (calls for service, population of data & demographics) • Generate projections for deployment & resource allocation CPAL- CSU San Bernardino

  17. Source: Hayes, (2001). “Patrol Deployment/ Redistricting ®” IACA Training Conference, Long Beach Sept. 20th 2001. CPAL- CSU San Bernardino

  18. Academic or Administrative • reports or statistical summaries for grant funding, commanders & public • Policy implications beyond law enforcement CPAL- CSU San Bernardino

  19. Source: Bueermann, J. (1999). Mapping for Managers. CMRC 10th Annual Conference. CPAL- CSU San Bernardino

  20. III. Challenges to Using GIS Ethical Issues • Redlining • Privacy Issues/Liability Technological limitations • Learning curve • Data Compatibility (format) Data Limitations • Large scales/ detail of basemaps • Availability and Currency • Lack of micro-level data CPAL- CSU San Bernardino

  21. Advantages Public awareness Partnerships Involvement/ Empowerment Accountability Disadvantages Privacy Commercialization Redlining Insurance rates Misinterpretation Making Data & Mapping Available to the Community CPAL- CSU San Bernardino

  22. There are some important things that you needto know about before using this data! • ALL ASPECTS OF THE DATA PROVIDED HEREIN ARE SUSCEPTIBLE TO A DEGREE OF ERROR DUE TO THE COMPLEXITIES OF THE PROCESS INVOLVED IN COMPILING AND PROGRAMMING THE DATA. NO WARRANTY, REPRESENTATION OR GUARANTY IS MADE OR IMPLIED REGARDING THE CONTENT, SEQUENCE, ACCURACY, TIMELINESS OR COMPLETENESS OF THE DATA PROVIDED HEREIN. • THIS VISUAL PRESENTATION OF DATA IS BEING PROVIDED STRICTLY AS A COURTESY, AND NOT AS AN OBLIGATION, TO ITS READERS. THE POLICE DEPARTMENT DOES NOT HAVE STAFF AVAILABLE TO ASSIST IN THE INTERPRETATION OF THE DATA PRESENTED HEREIN • I have read and understand the above Continue I do not wish to continue Back to main menu • Sacramento Police Department http://citymaps.sacto.org/GISAPPS2/cdisclaimer.htm CPAL- CSU San Bernardino

  23. Data Limitations impact Problem Solving • Lack of micro-level data in digital form • Aggregation of community information Place Intensive Research LEADS TO CPAL- CSU San Bernardino

  24. Place Intensive Methods • Resource limitations • Scale & boundaries • Lost community context GIS Analysis • Aggregated information • Large scale analysis • Data and technological limitations SOLUTION Blended Approach CPAL- CSU San Bernardino

  25. Blended Approach Phase 1. Community-level Analysis Crime Analysis provides a framework and focus. Phase 2. Contextual-level Analysis Abbreviated User Analysis identifies micro, community level attributes that influence crime. CPAL- CSU San Bernardino

  26. Copies of this Presentation are available from: Crime Prevention Analysis Lab California State University San Bernardino cjrc.csusb.edu/CPAL/CPAL.html CPAL- CSU San Bernardino

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