Exploring associations between streetscape factors and crime behaviors using Google Street View images  

作　　者：Mingyu Deng Wei Yang Chao Chen Chenxi Liu 

机构地区：[1]School of Computer Science,Chongqing University,Chongqing,400044,China [2]School of Management Science and Real Estate,Chongqing University,Chongqing,400044,China [3]State Key Laboratory of Mechanical Transmission,Chongqing University,Chongqing,400044,China

出　　处：《Frontiers of Computer Science》2022年第4期45-58,共14页中国计算机科学前沿（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant No.61872050,No.62172066);the Chongqing Basic and Frontier Research Program(cste2018jcyjAX0551),the FundamentaRl esearchFundsforthe,Central Universityes(2018CDJSK03XK01);the Chongqing Technology Innovation and Application Development Key Project(ctsc2019jscx-gksbx0066)。

摘　　要：Understanding the influencing mechanism of the urban streetscape on crime is fairly important to crime prevention and urban management.Recently,the development of deep learning technology and big data of street view images,makes it possible to quantitatively explore the relationship between streetscape and crime.This study computed eight streetscape indexes of the street built environment using Google Street View images firstly.Then,the association between the eight indexes and recorded crime events was revealed with a poisson regression model and a geographically weighted poisson regression model.An experiment was conducted in downtown and uptown Manhattan,New York.Global regression results show that the influences of Motorization Index on crimes are significant and positive,while the effects of the Light View Index and Green View Index on crimes depend heavily on the socioeconomic factors.From a local perspective,the Pedestrian Space Index,Green View Index,Light View Index and Motorization Index have a significant spatial influence on crimes,while the same visual streetscape factors have different effects on different streets due to the combination differences of socioeconomic,cultural and streetscape elements.The key streetscape elements of a given street that affect a specific criminal activity can be identified according to the strength of the association.The results provide both theoretical and practical implications for crime theories and crime prevention efforts.

关 键 词：CRIME Google Street View STREETSCAPE spatial analysis geographically weighted poisson regression 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] TP931.77[自动化与计算机技术—计算机科学与技术]