Measurement of Street Greenness and Interface Permeability Based on Street View Image Analysis

With the rapid advancement of urbanization, the spatial quality and ecological environment of urban streets have garnered increasing attention.Street greenness and street interface permeability are critical indicators for assessing the ecological environment and spatial quality of streets, playing a significant role in enhancing urban livability.Street view image analysis provides an intuitive and effective method for evaluating these metrics.However, existing research methods face challenges in handling large-scale street view images and complex scenarios, particularly concerning the precision and efficiency of semantic segmentation.This study aims to employ deep learning techniques to perform semantic segmentation on street view images, thereby measuring street greenness and interface permeability.The findings will offer scientific support for urban planning and the formulation of green city policies, holding substantial theoretical and practical value.