Street view imagery (SVI) has emerged as crucial micro-scale, human-perspective spatial data for urban analysis. However, most current research directly applies existing computer vision models to extract pixel ratios of objects, neglecting 3D information and spatial facilities essential for urban climate and mobility studies. My research leverages SVIs extracting 3D metrics and urban facilities to create novel methods serving sustainable urban development.