Static or dynamic? Characterize and forecast the evolution of urban crime distribution

作者：

Highlights：

• Development of a model to forecast short-term crime in a community network.

• Decomposing time series and capturing spatial patterns within decompositions.

• Utilizing taxis to proxy mobility within and between communities.

• Explaining how crime distribution change within and across communities.

摘要

•Development of a model to forecast short-term crime in a community network.•Decomposing time series and capturing spatial patterns within decompositions.•Utilizing taxis to proxy mobility within and between communities.•Explaining how crime distribution change within and across communities.

论文关键词：Urban crime,Spatiotemporal framework,Crime distribution,Graph neural network

论文评审过程：Received 7 July 2021, Revised 4 September 2021, Accepted 16 October 2021, Available online 12 November 2021, Version of Record 16 November 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116115