INVESTIGATING THE INFLUENCE OF TREE COVERAGE ON PROPERTY CRIME: A CASE STUDY IN THE CITY OF VANCOUVER, BRITISH COLUMBIA, CANADA
Keywords: Crime Mapping, LiDAR, GIS, Urban Vegetation, Spatial Lag, Geographically Weighted Regression
Abstract. With the development of Geographic Information Systems (GIS), crime mapping becomes an effective approach to investigate the spatial pattern of crime in a defined area. Understanding the relationship between crime and its surrounding environment can reveal possible strategies that can reduce crime in a neighbourhood. The relationship between vegetation density and crime has been under debate for a long time. This research is conducted to investigate the impacts of tree coverage on property crime in the City of Vancouver. High spatial resolution airborne LiDAR data collected in 2013 was used for the extraction of tree covered area for cross-sectional analysis. The independent variables were put into Ordinary Least-Squares (OLS) regression, Spatial Lag regression, and Geographically Weighted Regression (GWR) models to examine their influences on property crime rates. According to the results, the cross-sectional analysis demonstrated statistical evidences that property crime rates had negative correlations with tree coverage, with greater influences occurred around Downtown Vancouver.