Understanding the influencing mechanism of the urban streetscape on crime is fairly important to crime preven-tion 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 regres-sion 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 signifi-cant and positive,while the effects of the Light View Index and Green View Index on crimes depend heavily on the socio-economic factors.From a local perspective,the Pedestrian Space Index,Green View Index,Light View Index and Motoriza-tion 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 socio-economic,cultural and streetscape elements.The key streets-cape 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.

Mingyu DENG;Wei YANG;Chao CHEN;Chenxi LIU

School of Computer Science,Chongqing University,Chongqing 400044,China;School of Management Science and Real Estate,Chongqing University,Chongqing 400044,China;State Key Laboratory of Mechanical Transmission,Chongqing University,Chongqing 400044,China

计算机科学前沿

[1]Mingyu DENG;Wei YANG;Chao CHEN;Chenxi LIU-.Exploring associations between streetscape factors and crime behaviors using Google Street View images)[J].计算机科学前沿,2022(04):42-55

streetscape,uptown,Motorization,Motoriza

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