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Few studies have investigated how features of the land surface and the street network affect spatial crime patterns. Accordingly, for the current study, we estimated negative binomial regression models to test for main and moderating effects of elevation, slope, and betweenness on crime across San Francisco street segments. While significant effects were observed for all topography measures assessed, we found that elevation differences in the surrounding ¼ mile (i.e., hilliness) reduces the risk for crime more so than the elevation and slope of the segment itself. In comparison, betweenness based on the street network produced a higher risk for crime. We also determined a conditional effect between elevation differences in the surrounding ¼ mile and betweenness. To supplement the regression analysis, we produce maps that show the predicted values of the different crime outcomes for each segment in our sample, thereby underscoring certain policy and practical implications of our findings.

Topography and crime in place: The effects of elevation, slope, and betweenness in San Francisco street segments