Overview and Prospect for Spatial-Temporal Prediction of Crime

被引：0
作者：
Gu H. [1 ]
Chen P. [1 ]
Li H. [2 ]
机构：
[1] National Engineering Laboratory for Public Safety Risk Perception and Control by Big Data (PSRPC), Beijing
[2] School of Information Network Security, People's Public Security University of China, Beijing
来源：
Journal of Geo-Information Science | 2021年 / 23卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Big data; Crime prediction; Crime spatio-temporal risk; Environmental; Predictive methods; Predictive policing;
D O I：
10.12082/dqxxkx.2021.200247
中图分类号：
学科分类号：
摘要：
As the core technology of predictive policing, Spatial- Temporal (ST) prediction of crime has developed rapidly from around 2000 to the present. We introduce the basic theory of ST prediction of crime at the beginning. We regard the ST prediction method of crime as a process combining corresponding models to predict the ST distribution of crimes in the future and deconstruct it into relationships between three objects: case, ST backcloth, and individual behavior. Then, based on the input factors of prediction models, we sum up three current main methods, including ① the prediction method based on the information of cases' ST location, ② the prediction method based on the backcloth and the information of cases' ST location, and ③ the prediction method based on individual behavior, the backcloth, and the information of cases' ST location. We further summarize the mechanisms of different methods in detail respectively. In addition, we compare and analyze each method based on their applicable scenarios and predictive capacities. Finally, with the development of big data technology, we present solutions to improve current prediction methods, that are to construct a data- fusion system, refine data granularity, and integrate new types of data. For model optimization, we need to improve the ability of integrating heterogeneous data from multiple sources and balancing the interpretability and predictive ability of models. 2021, Science Press. All right reserved.
引用
收藏
页码：43 / 57
页数：14
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