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Elaborating Spatiotemporal Associations Between the Built Environment and urban vibrancy:A Case of Guangzhou City,China

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Chinese Geographical Science 2022年第3期32卷 480-492页

作者： WANG Bo LEI Yaqin XUE Desheng LIU Jixiang WEI Chunzhu School of Geography and Planning Sun Yat-sen UniversityGuangzhou 510275China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519000China Guangdong Provincial Key Laboratory of urbanization and Geo-simulation Guangzhou 510275China Department of urban Planning and Design the University of Hong KongHong Kong 999077China

This study applies multi-source datasets(i.e.,Baidu Heat Map data,points of interest(POIs)data,and floor area and land use data)and geographically and temporally weighted regression(GTWR)models to elaborate the spatiotemporal relationships between the built environment and urban vibrancy on both weekdays and weekends,using Guangzhou City as a ***,we verified the spatially and temporally nonstationary nature of the built environment correlates,which have been largely ignored in previous studies based on local regression *** spatially and temporally heterogeneous effects of the built environment on urban vibrancy are then presented and visualized,based on the GTWR *** found that the elasticity of location(i.e.,distance),land use mix(i.e.,diversity),building intensity and numbers of POIs with various functions(i.e.,density)are different across time(2-h intervals within a day)and space(grids),due to people’s everyday lifestyle,time-space constraints,and geographical context(e.g.,spatial structure).The findings highlight the importance of a better understanding of the local geography on the spatiotemporal relationships for urban planners and local governments so as to put forward decision-making support for fostering and maintaining urban vibrancy.

关键词： urban vibrancy Baidu Heat Map(BHM) built environment heterogeneity geographically and temporally weighted regression

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Exploring metro vibrancy and its relationship with built environment:a cross-city comparison using multi-source urban data

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Geo-Spatial Information Science 2022年第2期25卷 182-196页

作者： Wei Tu Tingting Zhu Chen Zhong Xiaohu Zhang Yang Xu Qingquan Li Guangdong Key Laboratory of urban Informatics and Shenzhen Key Laboratory of Spatial Smart Sensing and ServiceSchool of Architecture and Urban PlanningShenzhen UniversityShenzhenChina Ministry of Natural Resources(MNR)Key Laboratory for Geo-Environmental Monitoring of Great Bay Area Shenzhen UniversityShenzhenChina The Bartlett Centre for Advanced Spatial Analysis(CASA) University College London(UCL)LondonUK Department of urban Planning and Design The University of Hong KongHong KongChina Department of Land Surveying and Geo-Informatics The Hong Kong Polytechnic UniversityHong Kong SARChina

Recent urban transformations have led to critical reflections on the blighted urban infrastruc-tures and called for re-stimulating vital urban ***,the metro has been recognized as the backbone infrastructure for urban mobility and the associated economy *** date,limited research has been devoted to investigating the relationship between metro vitality and built environment in mega-cities *** paper presents a multisource urban data-driven approach to quantify the metro vibrancy and its association with the underlying built *** smart card data is processed to extract metro ridership,which denotes the vibrancy around the metro station in physical *** media check-ins are crawled to measure the vitality of metros in virtual *** physical and virtual vibrancy are integrated into a holistic metro vibrancy metric using an entropy-based weighting *** built environment characteristics,including land use,transportation and buildings are modeled as independent *** significant influences of built environ-mental factors on the metro vibrancy are unraveled using the ordinary least square regression and the spatial lag *** experiments conducted in Shenzhen,Singapore and London,this study comes up with a conclusion that spatial distributions of metro vibrancy metrics in three cities are spatially *** regression analysis suggests that in all the three cities,more affluent urban areas tend to have higher metro virbrancy,while the road density,land use and buildings tend to impact metro vibrancy in only one or two *** results demonstrate the relationship between the metro vibrancy and built environment is affected by complex urban *** findings help us to understand metro vibrancy thus make proper policy to re-stimulate the important metro infrastructure in the future.

关键词： urban vibrancy spatial-autocorrelation spatial lag model smart card data social media

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