发布时间：

2026-06-30

DOI码：

10.1111/gean.12187

所属单位：

城市与环境科学学院

论文名称：

Crime Exposure Along My Way Home: Estimating Crime Risk Along Personal Trajectory by Visual Analytics

发表刊物：

Geographical Analysis

摘要：

Crime has been one of the notorious public threats in cities. Fortunately, the increasing digital crime data provide great opportunities to analyze and control crime incidents. However, studies that predict the risk of crime exposure for an individual's spatiotemporal paths based on historical crime big data are still limited. In this study, we have proposed the crime risk index (CRI) for spatiotemporal trajectory and built a model to estimate the CRI. Furthermore, an online crime risk analysis platform has been developed based on the model. First, we proposed a multi-scale tile system and a novel algorithm to estimate trajectory-based CRI using big historical crime data and entropy-based weighting. Second, we created a web-based platform that allows users to provide a spatiotemporal trajectory and estimate the crime risk for such trajectory. We conducted several experiments based on the crime data in Detroit. Results demonstrate the practicability and generalizability of our platform. The proposed model and platform can be applied to multiple cities, providing useful references for crime information and public safety.

合写作者：

Zhou, Xiaolu

第一作者：

肖佳

论文类型：

期刊论文

论文编号：

1570660149377503232

文献类型：

00001

卷号：

52

期号：

01

页面范围：

49-68

ISSN号：

0016-7363

是否译文：

否

发表时间：

2020-01-01

收录刊物：

其他（ESI、Scopus、OA）、SSCI