City-Scale Mapping of Urban Façade Color Using Street-View Imagery

Precise urban façade color is the foundation of planning. Nevertheless, existing research on colors usually relies manual sampling due to technical limitations, which brings challenges for evaluating with co-existence city-scale and fine-grained resolution. In this study, we propose a deep learning-based approach mapping using street-view imagery. The dominant (DCUF) adopted as an indicator describe color. A case study in Shenzhen was conducted measure Baidu Street View (BSV) panoramas, both irregular geographical units regular grids. Shenzhen’s has gray tone low chroma. results demonstrate that proposed method high level accuracy extraction short, contributes development planning by efficiently analyzing higher levels validity across areas. Insights into from humanistic perspective could facilitate quality space design.