Revisiting the Spatial Analysis of Crime in National Forests
We examined spatial patterns of crime incidents in national forests covering 112,396 km2 in the northwestern United States. In this study we analyzed a database containing 40,003 spatially referenced crime incidents representing felonies, infractions, and misdemeanors during 2 calendar years (2003–2004) at several geographic scales. We applied several geospatial analytical techniques including quadrat analysis, nearest neighbor analysis (NNA), and nearest neighbor hierarchical (NNH) clustering to investigate crime incident spatial patterning. These geospatial tools were beneficial in identifying crime incident relationships contained within a large, complex spatial database. NNH clustering identified 15 regional clusters with 16,138 crime incidents, focused in the central portion of Oregon's national forests, specifically in the Deschutes, Mount Hood, and Willamette National Forests. Subsequent NNA tests confirmed spatial patterning in all three forests. Closer examination of a confirmed hot spot in one forest revealed a recreation corridor with adjacent recreation destination amenities and a large proximate metropolitan area, a combination of circumstances not apparent at the initial regional analysis scale. Other spatial data layers, such as transportation, urban boundaries, and water bodies, augmented our ability to understand, interpret, and validate geospatial analysis results. Spatial statistical analysis of crime incidents provides managers with a better understanding of the relationships between crime patterns, natural resources, and human built environments/infrastructure. Spatial statistical analysis can contribute to natural resource law enforcement as the basis for a decision support system. Decision support efforts include identifying places where crime is prevalent and determining where crime occurs with greatest frequency.
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Document Type: Research Article
Publication date: 2008-03-01
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