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基于多源数据的城市活力空间特征及建成环境对其影响机制研究
引用本文:王娜,吴健生,李胜,王宏亮,彭子凤.基于多源数据的城市活力空间特征及建成环境对其影响机制研究[J].热带地理,2021,41(6):1280-1291.
作者姓名:王娜  吴健生  李胜  王宏亮  彭子凤
作者单位:1.北京大学 深圳研究生院 城市规划与设计学院 城市人居环境科学与技术重点实验室,广东 深圳 518055;2.深圳市规划国土 房产信息中心,广东 深圳 518040;3.北京大学 城市与环境学院 地表过程与模拟教育部重点实验室,北京 100871
基金项目:国家重点研发计划项目(2019YFB2102000)
摘    要:采用城市POI、手机信令数据及夜间灯光遥感数据,以深圳市为例,构建城市活力度量指标分析城市活力的空间特征。构建“5D”指标体系度量城市建成环境,并运用地理探测器,探究建成环境对城市活力的影响机制。结果表明:1)深圳市城市综合活力显示出“南强北弱,西强东弱”的空间分异特征,空间分布极不均衡。城市综合活力最主要反映的是社会活力。2)城市综合活力、经济活力、社会活力、文化活力均受到建成环境的显著影响。高POI密度、高建筑密度、高平均建筑层数和高土地利用混合度对城市活力具有显著促进作用。3)居住人口密度与路网密度、土地利用混合度与路网密度等交互作用对城市活力产生更为积极的影响。4)在影响机制中,建筑密度、平均建筑层数为底层支撑因素,POI密度、土地利用混合度为直接驱动因素,居住人口密度为诱发因素,距行政区中心距离、交叉口密度、路网密度、地铁站点密度和公交站点密度为调节因素。

关 键 词:多源数据  城市活力  建成环境  影响机制  深圳市  
收稿时间:2021-03-20

Spatial Features of Urban Vitality and the Impact of Built Environment on Them Based on Multi-Source Data: A Case Study of Shenzhen
Na Wang,Jiansheng Wu,Sheng Li,Hongliang Wang,Zifeng Peng.Spatial Features of Urban Vitality and the Impact of Built Environment on Them Based on Multi-Source Data: A Case Study of Shenzhen[J].Tropical Geography,2021,41(6):1280-1291.
Authors:Na Wang  Jiansheng Wu  Sheng Li  Hongliang Wang  Zifeng Peng
Institution:1.Key Laboratory for Urban Habitat Environmental Science and Technology, School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China;2.Shenzhen Municipal Planning and Land Real Estate Information Center, Shenzhen 518040, China;3.Key Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
Abstract:As a key index to evaluate whether a city is attractive or has a healthy, comprehensive, and sustainable development potential, urban vitality is critical to the future development and construction of a city. Exploring the mechanism of how the built environment influences urban vitality from the perspective of urban morphology can be conducive to future urban space planning and design and can provide city planners with quantitative and scientific decision-making support. This study uses urban POI, cellular signaling, and nighttime light remote sensing data from Shenzhen to measure its cultural, social, and economic vitality, which constitutes a comprehensive vitality assessment of the city. Spatial features of these urban vitalities were then analyzed to further illustrate their distribution patterns. Using Bivariate Moran's I method, the spatial autocorrelations between economic, social, and cultural vitality were calculated. From the five dimensions of Density, Design, Diversity, Distance to Transit, and Destination Accessibility, the 5D detection index system was constructed to measure the urban built environment. This study also used GeoDetector to detect and analyze the spatial differentiation between various built environmental factors and comprehensive, economic, social, and cultural vitality and to explore the mechanism of the influence of the built environment on urban vitality. The results show that: 1) The spatial distribution of comprehensive vitality is extremely uneven in Shenzhen, with a higher vitality in the southern and western regions of Shenzhen city and a lower vitality in the northern and eastern regions. Areas with higher comprehensive vitality usually developed along the main roads and metro lines and are distributed in strips along the coastline of central-southern and western Shenzhen. The high-value areas of the urban comprehensive vitality center are primarily concentrated in city- or district-level commercial centers, and employment centers. Comprehensive vitality in Shenzhen reflects social vitality. 2) Urban comprehensive, economic, social, and cultural vitality are significantly affected by the built environment, as indicated by the 5D system. High POI and building density, average building floors, and land use entropy, have significant positive impacts on urban vitality. However, residential population density did not have a significant impact on each aspect of urban vitality. 3) Some interactions between built environment factors had a greater impact on urban comprehensive vitality, such as residential population density, road network density, land use entropy, and road network density. Overall, the interaction between building density, average building floors, land use entropy, and other factors, have a more positive impact on each aspect of urban vitality. 4) The presentation of urban comprehensive vitality is the result of multiple dimensions and factors. In the influencing mechanism of urban comprehensive vitality, building density and average building floors were the fundamental factors. POI density and land use entropy were the direct driving factors. Residential population density was an inducing factor. Distance from the administrative center, intersection density, road network density, metro station density, and bus station density were adjustive factors. The research results therefore provide valuable suggestions for the optimal allocation of resources and the rational layout of urban functional facilities in Shenzhen.
Keywords:multi-source data  urban vitality  built environment  influencing mechanism  Shenzhen  
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