Crime Analysis and Criminal Investigative Analysis

2021 ◽  
pp. 324-372
Author(s):  
G. W. Hildebrand
2016 ◽  
Vol 27 (3) ◽  
pp. 422-450 ◽  
Author(s):  
MOHAMMAD A. TAYEBI ◽  
UWE GLÄSSER ◽  
MARTIN ESTER ◽  
PATRICIA L. BRANTINGHAM

Crime reduction and prevention strategies are vital for policymakers and law enforcement to face inevitable increases in urban crime rates as a side effect of the projected growth of urban population by the year 2030. Studies conclude that crime does not occur uniformly across urban landscapes but concentrates in certain areas. This phenomenon has drawn attention to spatial crime analysis, primarily focusing on crime hotspots, areas with disproportionally higher crime density. In this paper, we present CrimeTracer1, a personalized random walk-based approach to spatial crime analysis and crime location prediction outside of hotspots. We propose a probabilistic model of spatial behaviour of known offenders within their activity spaces. Crime Pattern Theory concludes that offenders, rather than venture into unknown territory, frequently select targets in or near places they are most familiar with as part of their activity space. Our experiments on a large real-world crime dataset show that CrimeTracer outperforms all other methods used for location recommendation we evaluate here.


2017 ◽  
Vol 55 (2) ◽  
pp. 205-219 ◽  
Author(s):  
Swikar Lama ◽  
Sikandar Singh Rathore

AbstractThis study is based on crime mapping and crime analysis of property crimes in Jodhpur. The property crimes which were selected were house breaking, auto thefts and chain snatching. Data from police stations were used to generate the maps to locate hot spots of crimes. The profile of these hot spots was analyzed through observations supplemented with interviews of police officers and public 100 cases of house breaking and 100 cases of auto thefts were further analyzed to understand the contexts which lead to these crimes. These contexts are in consonance with situational crime prevention theories. This study may help to understand the environmental factors which may be responsible for certain places becoming hot spot areas of property crimes in Jodhpur.


2017 ◽  
Vol 18 (1) ◽  
pp. 9-26
Author(s):  
Lenin Heredia G. ◽  
Germán E. Bravo C.

Hotspots analysis is essential in the criminology field and quite important in decisions making for police agencies because it permits the enhancement of allocation of police resources for timely and adequate actions. There exist different techniques for analysis and generation of hotspots, limited by its difficulty to consider other urban and demographic factors that could be the cause of the emergence of these hotspots or their influence over other factors. On the other hand, it is also difficult and unusual to analyze hotspots in a temporal context. This paper seeks, through spatial-temporal operations based in hotspots, to go beyond of classical crime analysis with hotspots, by looking for the spatial influence of other spatial factors over and analyzing also their relationship in a temporal context. The paper initially presents and analyze the performance of various techniques for hotspot generation and determines that STAC technique from CrimeStat is the more suitable for the proposed objective. Then, it defines a hotspot algebra allowing the combined study of crime and spatial factors affecting it and/or been affected by crime events. Temporal analysis includes the hotspots generation for days of the week and/or months in a year. In this way it is possible to study causality relationships and/or correlations among the studied phenomena and the spatial-temporal environment where crime occurs. Therefore, it is possible to define and apply informed actions, primarily concerning the allocation of police resources. Finally, it shows some application examples, thematic as well as temporal analysis, of hotspot algebra using crime data from Bogota for the years 2011 to 2013; finally, some future works in the subject are proposed.


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