城市建筑2024，Vol.21Issue(5)：64-66,3.DOI:10.19892/j.cnki.csjz.2024.05.14
大数据支持下的南京市江浦老城街道空间品质分析
Analysis on Street Space Quality in Jiangpu Old City of Nanjing Supported by Big Data
摘要
Abstract
In the past decades of rapid urbanization, with the continuous expansion of the city, many streets have lost their social functions due to more attention to their traffic role in the construction, which has led to poor walking experience, decreased street perception and other problems. How to improve the quality of street space in a targeted and systematic way and inject new vitality into streets has become an important issue in building a livable city. This paper takes how to improve the street space quality of the old city as the research direction, selects the streets in Jiangpu Old City, Nanjing as the research case, and analyzes the street space quality by combining machine learning algorithm with street scene data. Based on the analysis results, the paper proposes the street space quality improvement strategies from four aspects: the street interface enclosure, the facility allocation, the green visibility, and the sky visibility.关键词
大数据/街道空间/机器学习/街道活力Key words
big data/street space/machine learning/street vitality分类
建筑与水利引用本文复制引用
谢宇川,朱隆斌..大数据支持下的南京市江浦老城街道空间品质分析[J].城市建筑,2024,21(5):64-66,3.
