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Crime at train stations: The role of passenger presence
Public transit stations are places that are known to generate opportunities for crime. By spatially integrating crime data, smart card data and census data along with information from OpenStreetMap and Queensland Rail, we apply multilevel negative binomial regression models to examine the role of pa...
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Published in: | Applied geography (Sevenoaks) 2022-03, Vol.140, p.102666, Article 102666 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Public transit stations are places that are known to generate opportunities for crime. By spatially integrating crime data, smart card data and census data along with information from OpenStreetMap and Queensland Rail, we apply multilevel negative binomial regression models to examine the role of passenger presence on the three most common types of crime at train stations in Brisbane, Australia. The findings reveal that passenger presence is differentially related to drug offences, public nuisance and theft. On weekdays, the number of passengers is negatively associated with drug offences and public nuisance, whereas it is positively associated with theft. During weekends and public holidays, public nuisance increases with the rising number of passengers, while passenger presence is not significantly related to the occurrence of drug offences and theft. The findings are important in their capacity to direct the development of appropriate crime prevention interventions.
•Crime at train stations clusters in space and time, but the pattern varies by crime type.•The impact of passenger presence on crime also varies by crime type.•Passenger presence is negatively associated with drug offences and public nuisance, but positively associated with theft.•Environmental characteristics at station, vicinity and neighbourhood level, contribute to specific crime type at stations. |
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ISSN: | 0143-6228 1873-7730 |
DOI: | 10.1016/j.apgeog.2022.102666 |