Street luminosity influence on reported thefts from vehicles during night-time

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesCriminality across many urban settings has created the need to develop tools that help better understand the social and physical determinants of crime. One specific aspect is how certain urban characteristics may influence criminal activities. One facet of the built environment, street lighting, influences the perception of safety for a potential victim, and it also influences a perpetrator´s risk analysis, affecting how it envisions both costs and rewards for committing a crime. The study looked into the relationship between street illuminance levels, through street light pole density as a proxy, and other crime determinants and the prevalence of reported Night-Time Theft from Vehicle crimes in Vancouver, BC, Canada, through exploratory spatial data analysis and by fitting Geographically Weighted Poisson Regressions. To test if street lighting pole density is a usable proxy for street illuminance it also modeled the relationship between street lighting pole and tree densities and measured night time street illuminance by fitting an Ordinary Least Squares regression. Night time street illuminance was measured using a specially built georeferenced mobile illuminance collection station based on the senseBox. Findings suggest that while a citywide effect is evident for some of the explanatory variables, there is an evident nonstationary relation between the explanatory variables and Night-Time Theft from Vehicle crimes in Vancouver. Regarding street lighting, regressions suggest it may not be an important covariate with Night-Time Theft from Vehicle crime. Coefficients are quite heterogenous throughout with most of the study area showing a mix of weak to mild positive association, specially on the East side, and weak to mild negative associations. The OLS regression showed a moderately weak relation between light poles and tree densities to collected street illuminance. The question of street lighting pole density being a usable proxy for street illuminance could not be answered with confidence

Crime and Greenspace: Extending the Analysis Across Cities

The role of greenspace in urban areas has become a focus of research as municipalities seek to increase the quality of life in cities. Multiple benefits are found to be associated with greenspace, but disservices such as crime are often overlooked. Studies investigating the link between crime and greenspace have revealed mixed results and been limited in geographic scope. This dissertation sought to examine the crime and greenspace relationship, extending the analysis to multiple cities in order to describe how the relationship may vary in different contexts. Additionally, one possible cause of crime, increased temperatures, was investigated to determine how greenspace may moderate the impact of hot weather on crime risk. As urban parks are an important type of greenspace, the relationship between proximity to parks and crime was examined in four case cities. Parks are typically green areas of cities but also encompass less green land uses. This broad analysis revealed a more comprehensive understanding of how crime and greenspace are related which can inform residents and decision-makers of the benefits and possible drawbacks from including greenspace in city and community development

Investigating the Influences of Tree Coverage and Road Network Density on Property Crime: A Case Study in the City of Vancouver, British Columbia, Canada

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. On the one hand, dense vegetation is usually used as shield by criminals when committing crime. On the other hand, green spaces can attract people to spend time outdoors and thus create nature surveillance around the area. The convenience of road network is another important factor that can influence criminal’s selection of locations. This research investigates the impacts of tree coverage and road network density on crime in the City of Vancouver. Temporal analysis was conducted based on detected vegetation changes and crime data from 2008 to 2013. High spatial resolution airborne LiDAR data collected in 2013 provided by the City of Vancouver and road network file provided by Statistics Canada were used for the extraction of tree-covered area and the calculation of road density for cross-sectional analysis. The two 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. Other independent variables taken into consideration included population density, unemployment rate, lone-parent families, low-income families, streetlights and graffiti. According to the results, the temporal analysis provided qualitative evidence of vegetation coverage having inverse impact on property crime, and the cross-sectional analysis demonstrated statistical evidences that property crime rates had negative correlations with both tree coverage and road density, with greater influences occurred around Downtown Vancouver

Investigating the Influences of Tree Coverage and Road Density on Property Crime

With the development of Geographic Information Systems (GIS), crime mapping has become an effective approach for investigating the spatial pattern of crime in a defined area. Understanding the relationship between crime and its surrounding environment reveals possible strategies for reducing crime in a neighborhood. The relationship between vegetation density and crime has long been under debate. The convenience of a road network is another important factor that can influence a criminal’s selection of locations. This research is conducted to investigate the correlations between tree coverage and property crime, and road density and property crime in the City of Vancouver. High spatial resolution airborne LiDAR data and road network data collected in 2013 were used to extract tree covered areas for cross-sectional analysis. The independent variables were inserted into Ordinary Least-Squares (OLS) regression, Spatial Lag regression, and Geographically Weighted Regression (GWR) models to examine their relationships to property crime rates. The results of the cross-sectional analysis provide statistical evidence that there are negative correlations between property crime rates and both tree coverage and road density, with the stronger correlations occurring around Downtown Vancouver

Crime and Fear in Public Places

No city environment reflects the meaning of urban life better than a public place does. A public place, whatever its nature – a park, a mall, a train platform or a street corner – is where people pass by, meet each other and at times become a victim of crime. With this book, we submit that crime and safety in public places are not issues that can be easily dealt with within the boundaries of a single discipline. The book aims to illustrate the complexity of patterns of crime and fear in public places with examples of studies on these topics contextualized in different cities and countries around the world. This is achieved by tackling five crosscutting themes: the nature of the city’s environment as a backdrop for crime and fear; the dynamics of individuals’ daily routines and their transit safety; the safety perceptions experienced by those who are most in fear in public places; the metrics of crime and fear; and finally, examples of current practices in promoting safety. All these original articles contribute to our quest for safer, more inclusive, resilient, equitable and sustainable cities and human settlements aligned to the Global 2030 Agenda for Sustainable Development