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Risikoterrænmodellering×Kriminalitetslinkageanalyse×
FagområdeForensikForensik
FamilieProcess / pipelineProcess / pipeline
Oprindelsesår20112002
OphavspersonJoel CaplanCraig Bennell
TypeGeographic information systems and crime science methodCrime science and offender profiling method
Oprindelig kildeCaplan, 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 ↗Bennell, C., Canter, D. V., & Alison, L. J. (2002). Linking commercial burglaries by modus operandi: Tests using regression and ROC analysis. Science and Justice, 42(3), 153-164. DOI ↗
Aliasserenvironmental criminology, RTM analysis, crime risk mappingcase linkage, offender linking, serial crime attribution
Relaterede33
ResuméRisk 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.Crime linkage analysis is a forensic method that determines whether a series of crimes were committed by the same offender based on behavioral and modus operandi (MO) similarities. Developed systematically by Craig Bennell and colleagues in the early 2000s, crime linkage applies statistical and similarity-matching techniques to establish offender attribution. The method is essential in serial crime investigation, where establishing linkage enables consolidation of investigation resources, geographic profiling, and offender-focused surveillance.
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ScholarGateSammenlign metoder: Risk Terrain Modeling · Crime Linkage Analysis. Hentet 2026-06-18 fra https://scholargate.app/da/compare