Urbanization is one of the main drivers of global economic growth. More than half of the world’s population currently lives in urbanized areas, and many economic activities are now concentrated in urban areas. On the other hand, the patterns of crime are also linked to the patterns of urbanization. In many countries, crime occurs more frequently and concentrates in a city center. In addition, urban crime usually exhibits complexity and dynamics.
Bangkok is the capital and the primate city of Thailand. The number of crime reports in the city is also the highest. Urban safety is one of the critical concerns for the residents of Bangkok. Thus, more understandings of urban crime and security of Bangkok are needed to mitigate urban crime and improve the quality of life and socioeconomic development of the inhabitants and city.
This research aims to investigate the public perception of urban security. The perception bias of urban security is indicated by comparing the perception of safety and actual crime locations in an urban area in Bangkok using Thong Lor District as a study area. The relationship between urban structure and the spatial dimension of urban crime is analyzed using machine learning. The findings can be used as a guideline for urban security mapping and management.
Keywords: Perception bias, perception of crime, crime, urban security, machine learning, Bangkok