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	Crime Hot Spot Analysis	Hot Spot Analysis
Field	Criminology	Spatial analysis
Family	Process / pipeline	Regression model
Year of origin	1995	1992
Originator	Lawrence Sherman & David Weisburd (policing); Arthur Getis & J. Keith Ord (statistic)	Arthur Getis and J. Keith Ord
Type	Spatial cluster detection for crime concentration	Local spatial statistic
Seminal source	Sherman, L. W., & Weisburd, D. (1995). General deterrent effects of police patrol in crime "hot spots": A randomized, controlled trial. Justice Quarterly, 12(4), 625–648.	Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206.
Aliases	Hot Spot Mapping, Crime Hotspot Detection, Getis-Ord Gi* Crime Analysis, Spatial Cluster Analysis of Crime	Getis-Ord Gi* statistic, spatial hot spot detection, cluster and outlier analysis, HSA
Related	4	5
Summary	Crime hot spot analysis identifies the places where crime concentrates far more than chance — the small number of street segments, blocks, or addresses that account for a large share of incidents. Building on Sherman and Weisburd's landmark demonstration that crime clusters tightly in space and that patrolling those clusters deters offending, the method uses spatial statistics such as the Getis-Ord Gi* local statistic to separate genuine, statistically significant clusters from random noise and to classify each place as a hot spot, a cold spot, or neither.	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.