This report examines the evolution of crime mapping and predictive models, assessing their accuracy and potential for informing proactive policing and crime prevention.
(Generated with the help of GPT-4)
| Quick Facts | |
|---|---|
| Report location: | source |
| Language: | English |
| Publisher: |
National Institute Of Justice The Urban Institute |
| Authors: | Nancy G. La Vigne, Elizabeth R. Groff |
| Geographic focus: | Global |
The research method involved a literature review of existing crime mapping and predictive modeling methods, assessing their theoretical underpinnings, data requirements, and practical applications. The review also considered the accuracy of different methods and their potential to inform proactive policing strategies.
(Generated with the help of GPT-4)
The report reviews various methods used in predictive crime mapping, from simple hot spot identification to complex modeling techniques. It evaluates their accuracy, data requirements, and ease of use, aiming to guide future research and practical applications in crime forecasting.
(Generated with the help of GPT-4)
Categories: English publication language | Global geographic scope | artificial neural networks | computer mapping | crime | crime analysis | crime patterns | crime prediction | crime prevention | geographic information systems (gis) | high crime areas | hot spots | leading indicators | models | point process model | police crime analysis training | predictive crime mapping | proactive police units | proactive policing | raster gis methods | repeat victimization | univariate methods | victimization surveys