Geographic profiling is an investigative tool that can be seen as a strategic information management system to assist police with the large volume of information throughout an investigation. It concentrates its focus on the geographic aspects of the crime and was developed in response to the demands of solving serial crimes. In response, Rossmo developed a computerized geographic profiling algorithm called criminal geographic targeting (CGT) which assess the spatial characteristics of crimes. It analyzes the geographic coordinates of the offender’s crimes and produces a color map which assigns probabilities to different points for the most likely area of the offender’s home base. CGT has been patented and integrated into a specialized crime analysis software product called Rigel. The Rigel product is developed by the software company Environmental Criminology Research Inc. (ECRI), which Rossmo co-founded. Geographic Profilers often employ tools such as Rigel, CrimeStat or Gemini to perform geographic analysis. System inputs are crime location addresses or coordinates, often entered through a geographic information system (GIS). Output is a jeopardy surface (three-dimensional probability surface) or color geoprofile, which depicts the most likely areas of offender residence or search base. These programs assist crime analysts and investigators to focus their resources more effectively by highlighting the crucial geographic areas. This article uses material from the Wikipedia article "Geographic_profiling", which is released under the Creative Commons Attribution-Share-Alike License 3.0.
While the use of spatial analysis methods in police investigations goes back many years (think of detectives gathered around a large city map with pins stuck in it), the formalized process known today as geographic profiling originated out of research conducted at Simon Fraser University's School of Criminology in British Columbia, Canada, in 1989. Geographic profiling model is based on the assumption that offenders are more likely to select their victims and commit a crime which would be centered near their home address. The technique has now spread to several U.S., Canadian, British, and European law enforcement agencies. Originally designed for violent crime investigations, it is increasingly being used on property crime. Through numerous research studies, there has been an increased importance placed on the journeys offenders habitually take to determine the spatial range of criminal activity. These areas become a comfort zone for predatory offenders to commit their crime with a feeling of safety. Consequently, criminal acts follow a distance-decay function, such that the further away the regular activity space of an offender is, the less likely that the person will engage in a predatory criminal activity. However, there is also a buffer zone where an offender will avoid committing crimes too close to their homes in the likely event that they will be identified by a neighbour. Central concepts The theoretical foundation of geographic profiling is in environmental criminology Key concepts include: Journey-to-Crime Supports the notion that crimes are likely to occur closer to an offender’s home and follow a distance-decay function (DDF) with crimes less likely to occur the further away an offender is from their home base. It is concerned with the ‘distance of crime’ and that offenders will in general travel limited distances to commit their crimes. Routine Activity Theory Originally developed by Cohen and Felson (1979), the primary principle is that the offender and victim must intersect in time and space for a crime to occur. This approach focuses on the concept that crime occurs when an opportunity is taken within both parties’ non-criminal spatial activity. An activity space may consist of the regular areas an offender travels such as work, school, home or recreational areas. Rational Choice Theory Concepts relating to the explanation of spatial behaviour include the least-effort principle where offenders are more likely to act on the first or opportunity and the idea of a buffer zone. It exhibits a constant tension between the offender’s desire to divert attention from his home base and the desire to travel no further than necessary to commit crimes. Crime Pattern Theory Developed by Canadian environmental criminologists Paul and Patricia Brantingham, the theory exerts the strongest influence in geographic profiling. It suggests that crime sites and opportunities are not random. There is an emphasis in the interaction between the offender’s mental map of spatial surroundings and the allotment of victims (target backcloth). Furthermore, serial crimes are the easiest to develop geographic profiles, since each crime contains new spatial information and provides additional data including the fact that crime area tends to enlarge with an increase of comfort and confidence. The initial hunt and criminal acts are most likely to occur relatively close to the location of the offender’s home or workplace. As the success rate increases, there will be a burgeoning sense of confidence to seek his prey further from home and to travel a greater distance. Crimes that are suitable for analysis are those that are predatory in nature and exercises some spatial decision-making process such as the area for hunting targets, travel routes, mode of transportation and even body dump sites. Another leading researcher in this area is David Canter whose approach to geographic profiling detailed around the circle theory of environmental range. In 1993, Canter and Larkin developed two models of offender behaviour: marauder and commuter models. The distinction is that marauders operate in an area that is in close proximity of the offender’s home base while commuters commit crimes far outside of the habitual zone. It hopes to differentiate the two types of serial offenders by studying the relationship of the criminal spatial behaviour to the offender’s place of residence. This article uses material from the Wikipedia article "Geographic_profiling", which is released under the Creative Commons Attribution-Share-Alike License 3.0.