Citation

Zhang H, Zahnow R, Liu Y, Corcoran J. Appl. Geogr. 2022; 140: e102666.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.apgeog.2022.102666

PMID

unavailable

Abstract

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.

Language: en

Keywords

Drug offences; Passenger presence; Public nuisance; Theft; Train stations