This is the third of three chapters on "Spatial Descriptions" from the user manual for CrimeStat IV, a spatial statistics package that can analyze crime incident location data.
The chapter, "Distance Analysis I and II," describes the characteristics of the distances between points. The chapter focuses on "second-order" properties of distance analysis, which refers to sub-regional or "neighborhood" crime patterns within the overall distribution. Second-order characteristics show how particular crime incidents are concentrated in particular environments. The chapter has two sections on distance analysis. In Distance Analysis I, various second-order statistics are provided; and in Distance Analysis II, four routines for calculating and outputting distance matrices are discussed. Issues related to Distance Analysis I pertain to the nearest neighbor index, the K-order nearest neighbor, the linear nearest neighbor index, the linear K-order nearest neighbor index, and Ripley's "K" statistic. Assigning primary points to secondary points is also discussed under Distance Analysis I. Extensive figures display computer screens, and attachments discuss SARS (Severe Acute Respiratory Syndrome) and the distribution of passengers on an airplane; nearest neighbor analysis for "man with a gun" calls in Charlotte, NC, in 1989; and "K Function Analysis to Determine Clustering in the 'police confrontations' dataset in Buenos Aires Province, Argentina in 1989." 12 references
- Understanding the spatial distribution of crime based on its related variables using geospatial discriminative patterns
- Optimization of criminal hotspots based on underlying crime controlling factors using geospatial discriminative pattern
- Predicting dynamical crime distribution from environmental and social influences