Abstract：This study investigates the streets in the inner ring of Shanghai through multi-source data and image segmentation, intelligent recognition technology to explore the physical characteristics of the street, interface characteristics, urban functions, macro morphology and the individual's perception of the street amenity and build a mathematical model to identify key factors and values related to street perception. It finds that green viewing rate is a key factor affecting the street amenity, and building density and aspect ratio have a positive effect on the perception of the amenity. Through regression analysis of object index and amenity score, it obtains the critical index of spatial perception, so as to provide guidelines for street design in Shanghai.
方智果 贺丽洁 章丹音. 基于多源数据分析的上海街道空间宜人性测度与影响因素识别[J]. 新建筑, 2021, 39(5): 142-147.
FANG Zhiguo HE Lijie ZHANG Danyin. Measurement of Street Space Amenity and Identification of Influencing Factors in Shanghai Based on Multi-source Data. New Architecture, 2021, 39(5): 142-147.
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