Semantic Segmentation for Evaluating Street Elements in Shanghai’s “Golden Triangle” based on Streetscape Images
Year: 2025
Type: article
Abstract: The “Golden Triangle” along the Huangpu River (the Bund, Lujiazui, and North Bund) symbolizes Shanghai’s urban growth, yet its current developmental status is underexplored in academic research. This study employs semantic segmentation and GIS to analyze street elements in the area using streetscape images. Baidu Street View data was processed via Python to extract images from various orientations, segment key street elements, and calculate their distributions. GIS was then applied to evaluate their spatial distribution and urban development status. The research highlights the potential of semantic segmentation in urban analysis and decision-making.
Authors: Xintian Lyu, Zigang Yao
Institution: East China University of Science and Technology
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409206485