Comparar métodos

	Risk Terrain Modeling (Criminology)	Análisis de Puntos Calientes (Getis-Ord Gi*)
Campo	Criminology	Análisis espacial
Familia	Process / pipeline	Regression model
Año de origen	2011	1992
Autor original	Joel Caplan & Leslie Kennedy	Arthur Getis and J. Keith Ord
Tipo	Spatial risk-factor aggregation model for crime forecasting	Local spatial statistic
Fuente seminal	Caplan, J. M., Kennedy, L. W., & Miller, J. (2011). Risk terrain modeling: Brokering criminological theory and GIS methods for crime forecasting. Justice Quarterly, 28(2), 360–381.	Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206.
Alias	RTM, Risk Terrain Analysis, Environmental Risk Factor Modeling, Spatial Risk Factor Modeling	Getis-Ord Gi* statistic, spatial hot spot detection, cluster and outlier analysis, HSA
Relacionados	4	5
Resumen	Risk Terrain Modeling (RTM) represents crime risk as a function of the environment: it identifies the features of a landscape — bars, bus stops, vacant lots, pawn shops, schools — that attract or generate crime, maps each one's spatial influence as a separate risk layer, and combines those layers onto a raster of place to produce a relative risk surface. Introduced by Joel Caplan and Leslie Kennedy around 2011, RTM 'brokers' environmental criminology theory and GIS methods so that crime forecasting rests on the qualities of places rather than on the history of crime alone.	Hot Spot Analysis uses the Getis-Ord Gi* local spatial statistic to identify geographic locations where high or low attribute values cluster together to a degree that is statistically significant. Each feature is evaluated in relation to its neighbours, producing a z-score that flags genuine spatial hot spots and cold spots against a background of random variation.