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作者

Ning Niu;Li Li;Xiaojian Li;Jialin He

来源

CITIES,Vol.127,Issue1,Article 103771

语言

英文

关键字

Urban community vibrancy;Structural elements;Urban social and ambient elements;Local Entropy Map;Random Forest Regression

作者单位

School of Resources and Environment/Academician Laboratory for Urban and Rural Spatial Data Mining of Henan Province, Henan University of Economics and Law, Zhengzhou 450046, China;Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;International Ecosystem Management Partnership, United Nations Environment Programme, Beijing 100101, China;Key Research Institute of Yellow River Civilization and Sustainable Development/College of Geography and Environment, Henan University, Kaifeng 475001, China;School of Resources and Environment/Academician Laboratory for Urban and Rural Spatial Data Mining of Henan Province, Henan University of Economics and Law, Zhengzhou 450046, China;Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;International Ecosystem Management Partnership, United Nations Environment Programme, Beijing 100101, China;Key Research Institute of Yellow River Civilization and Sustainable Development/College of Geography and Environment, Henan University, Kaifeng 475001, China

摘要

Most of the existing studies captured the social and ambient elements of urban built environment, but rarely have the structural elements that influence community vibrancy been addressed. In this paper, we composed indices to assess community vibrancy in Guangzhou, China using population density, social- intensity, and economic activity intensity. We then utilized the Local Entropy Map and Random Forest Regression to investigate the spatial-temporal variation of vibrancy and how it relates to the communities' structural and social & ambient elements using social and remote sensing data. We found their relationships to be spatially dependent and contrasting between functionally different regions. Our analysis at the wholistic level revealed that the vibrancy of the city was influenced more by the social & ambient elements, while analysis at the functional-region level showed this to be also true for the commercial regions of the city, that of residential regions was influenced more by the structural elements. We argue that urban vibrancy should be treated at the functional- region level, and that the importance of structural elements and social and ambient elements should both be recognized in urban research and the policy-making process.