The Northern Virginia Military Shooting Series: Operational Validation of Geospatial Predictive Analytics

This 2013 article examines the case of a Marine Corps reservist who perpetrated a series of attacks against military facilities in Virginia in October and November 2010. The authors discuss how geospatial predictive analytics was considered in the case as an asset that could enable information-based decisions regarding resource allocation and optimization. By statistically characterizing the environments associated with previous or known incidents, the authors argue that geospatial predictive analysis allows the end user to identify statistically similar areas at increased likelihood for future, previous, or yet undetected incidents. The authors argue that the resulting model, allows the end user to focus resources on those areas that have an increased likelihood for a future incident. This so-called area reduction supports risk-based deployment, wherein resources are deployed specifically when and where they are likely to be needed.

This article will be of use to practitioners and researchers interested in geospatial predictive analytics and attack detection, prediction, prevention, and response within a security context. In contrast to other hot-spot methodologies, geospatial predictive analytics is presented as enabling analysts to identify new locations, including those that are not contiguous with previous events. The authors argue that this is particularly important as it provides the insight necessary to move from chasing crime, which may jump around the community in question, to being able to effectively anticipate activities and events in support of proactive approaches to prevention and response.