NDLI: Explore the Correlation between Environmental Factors and the Spatial Distribution of Property Crime

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Explore the Correlation between Environmental Factors and the Spatial Distribution of Property Crime

Content Provider	MDPI
Author	Sun, Lijian Zhang, Guozhuang Zhao, Dan Ji, Ling Gu, Haiyan Sun, Li Li, Xia
Copyright Year	2022
Description	Comprehensively understanding the factors influencing crime is a prerequisite for preventing and combating crime. Although some studies have investigated the relationship between environmental factors and property crime, the interaction between factors was not fully considered in these studies, and the explanation of complex factors may be insufficient. This paper explored the influence of environmental factors on property crime using factor regression and factor interaction based on data from the central city of Lanzhou, China. Our findings showed that: (1) The distribution of crime cases showed the pattern of a local multi-center. Shop density, hotel density, entertainment density and house price were the four dominant environmental drivers of property crime; (2) The relationship between the light intensity and property crime had different correlation explanations in temporal projection and spatial projection. There was a normal distribution curve between the number of property crimes and the Price-to-Earnings Ratio (PE Ratio) of the community house price; and (3) The results of the factor interaction indicated that the effect of all factors on crime showed a two-factor enhancement. As an important catalyst, shop density had the strongest interaction with other factors. Shop density gradient influenced the degree of interpretation of spatial heterogeneity of property crime.
Starting Page	428
e-ISSN	22209964
DOI	10.3390/ijgi11080428
Journal	ISPRS International Journal of Geo-Information
Issue Number	8
Volume Number	11
Language	English
Publisher	MDPI
Publisher Date	2022-07-28
Access Restriction	Open
Subject Keyword	ISPRS International Journal of Geo-Information Isprs International Journal of Geo-information Criminology and Penology Property Crime Environmental Factors Factor Interaction Bayesian Linear Regression (blr) Geo-detector Lanzhou
Content Type	Text
Resource Type	Article

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