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Моделирование местности риска (Risk Terrain Modeling, RTM)×Географическое профилирование×
ОбластьКриминалистикаКриминалистика
СемействоProcess / pipelineProcess / pipeline
Год появления20111994
Автор методаJoel CaplanDavid Canter
ТипGeographic information systems and crime science methodGeographic and spatial analytics method
Основополагающий источникCaplan, J. M., Kennedy, L. W., & Miller, J. (2011). Risk terrain modeling: Brokering criminological theory and GIS methods for crime forecasting. Journal of Research and Practice in Criminal Justice, 17(1), 56-69. link ↗Canter, D. V., & Hammond, L. (1994). Picking up the pieces: The identification of glass sources in forensic enquiries. Journal of Forensic Sciences, 39(4), 1018-1034. link ↗
Другие названияenvironmental criminology, RTM analysis, crime risk mappingspatial crime analysis, crime hotspot mapping
Связанные33
СводкаRisk Terrain Modeling (RTM) is a geospatial crime prediction method that identifies high-risk locations by analyzing environmental and geographic features that attract or facilitate crime. Developed by Joel Caplan, Lichen Kennedy, and James Miller in 2011, RTM bridges environmental criminology theory with geographic information systems (GIS) to create predictive risk maps. Unlike methods that predict offender location (e.g., geographic profiling), RTM predicts where crimes are likely to occur based on terrain characteristics, infrastructure, and social environmental factors.Geographic profiling is a spatial analysis method used in forensic investigation to locate offenders based on the locations of their crimes. Developed by David Canter in 1994, it combines geostatistics, probability theory, and crime pattern analysis to identify high-probability crime origin zones. The method has been widely adopted in law enforcement agencies across North America and Europe.
ScholarGateНабор данных
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  2. 3 Источники
  3. PUBLISHED
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ScholarGateСравнение методов: Risk Terrain Modeling · Geographic Profiling. Получено 2026-06-18 из https://scholargate.app/ru/compare