Research on the Measurement and Influencing Factors of Village Spatial Quality Based on Street View Perception

Abstract

Against the backdrop of the deepening implementation of the rural revitalization strategy, enhancing village spatial quality has become a core issue in improving living environments and boosting villagers' sense of well-being. This study adopts street scene perception as the central perspective, integrating subjective observations with objective analysis to construct a measurement system for village spatial quality and explore its influencing factors. First, it defines the core concepts of village spatial quality and street scene perception, laying the research foundation through theories such as human settlement science and environmental behavior studies. Second, a measurement index system is established across five dimensions: safety, comfort, vitality, uniqueness, and cleanliness. By combining off-site environmental audits with deep learning technologies, the study achieves quantitative measurement of indicators. The analytic hierarchy process is then used to determine weights and complete comprehensive evaluation. Third, influencing factors are selected from four dimensions: architecture, roads, facilities, and environment. Correlation analysis and regression models are employed to reveal their mechanisms in shaping both the overall spatial quality and its classification dimensions. Finally, the study summarizes key conclusions, proposes targeted recommendations for optimizing village spatial quality, and outlines future research directions. The findings provide scientific basis and technical support for rural spatial planning and human settlement improvement, enriching the methodological framework of rural spatial quality research.