Exploring the Complex Association Between Urban Built Environment, Sociodemographic Characteristics and Crime: Evidence from Washington, D.C.

The urban built environment and sociodemographic characteristics have complex relationships with urban crime. However, previous studies have had limitations such as generalizing urban green space types, urban functionality, and sociodemographic characteristics. Given these, this study aimed to explore the relationship between them using more detailed indicators. The study utilized Google Street View and points of interest to depict the built environment. Building on previous work that segmented natural and artificial elements in streetscape images, this study further distinguished trees, bush, and grass. Additionally, it incorporated data from the Data Analysis and Visualization Unit of the DC Office of Planning to reflect a broader range of individual characteristics. Weighted least squares regression and Pearson correlation analysis were used to test the relationship between the built environment, sociodemographic, and crime, respectively. Some of the key findings are as follows. (1) Trees, bushes, and grass all reduce crime. (2) Urban functionality is hard to curb crime by enhancing informal public surveillance. (3) Among the sociodemographic variables, the walking commute rate is the variable most strongly positively correlated with crime. (4) Family relationships play an important role in suppressing crime. This study examined a more comprehensive range of indicators affecting urban crime in favor of safer cities.

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Publication Details

Journal
Land
Published
2024-11-11
DOI
https://doi.org/10.3390/land13111886
Citations
7
Primary Topic
Crime Patterns and Interventions
Type
article
Field-Weighted Citation Impact
7.92

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article

Exploring the Complex Association Between Urban Built Environment, Sociodemographic Characteristics and Crime: Evidence from Washington, D.C.

Lei Wang, Longhao Zhang, Shangen Tsou, Kaixin Liu et al.
7 citations
Land
Crime Patterns and Interventions
7.92
article

Exploring the Complex Association Between Urban Built Environment, Sociodemographic Characteristics and Crime: Evidence from Washington, D.C.

Lei Wang, Longhao Zhang, Shangen Tsou, Kaixin Liu, Yike Hu, Ke Yang
article en
7 citations

Abstract

The urban built environment and sociodemographic characteristics have complex relationships with urban crime. However, previous studies have had limitations such as generalizing urban green space types, urban functionality, and sociodemographic characteristics. Given these, this study aimed to explore the relationship between them using more detailed indicators. The study utilized Google Street View and points of interest to depict the built environment. Building on previous work that segmented natural and artificial elements in streetscape images, this study further distinguished trees, bush, and grass. Additionally, it incorporated data from the Data Analysis and Visualization Unit of the DC Office of Planning to reflect a broader range of individual characteristics. Weighted least squares regression and Pearson correlation analysis were used to test the relationship between the built environment, sociodemographic, and crime, respectively. Some of the key findings are as follows. (1) Trees, bushes, and grass all reduce crime. (2) Urban functionality is hard to curb crime by enhancing informal public surveillance. (3) Among the sociodemographic variables, the walking commute rate is the variable most strongly positively correlated with crime. (4) Family relationships play an important role in suppressing crime. This study examined a more comprehensive range of indicators affecting urban crime in favor of safer cities.

LandVol. 13(11)
Tianjin University (CN), Jilin Jianzhu University (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 3%
Crime Patterns and Interventions
7.92
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Exploring the Complex Association Between Urban Built Environment, Sociodemographic Characteristics and Crime: Evidence from Washington, D.C. — Lei Wang, Longhao Zhang, et al. · Land (2024) | TGRS Research Map | TGRS