Influencing factors of urban safety perception based on the combination of multi-source data and machine learning: a case study of Nanchang City, China
Journal: Scientific Reports
Year: 2025

Research examines the influence of multisource urban data on residents' perceptions of safety. Utilizing the SHAP machine learning model, the research conducts a comprehensive analysis of the nonlinear relationships and interactive effects between built environment factors and psychological perception factors on urban residents' safety perceptions. Focusing on Nanchang City as a case study, the research integrates multidimensional data encompassing urban spatial environments, resident perception