Exploring metro vibrancy and its relationship with built environment: a cross-city comparison using multi-source urban data-Reference-Cited by-同舟云学术

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

Published:2021-12-03 Issue: Volume: Page:1-15
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Tu Wei¹²^ORCID,Zhu Tingting¹,Zhong Chen³^ORCID,Zhang Xiaohu⁴,Xu Yang⁵^ORCID,Li Qingquan¹²

Affiliation:

1. Guangdong Key Laboratory of Urban Informatics, and Shenzhen Key Laboratory of Spatial Smart Sensing and Service, School of Architecture and Urban Planning, Shenzhen University, Shenzhen, China

2. Ministry of Natural Resources (MNR) Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University, Shenzhen, China

3. The Bartlett Centre for Advanced Spatial Analysis (CASA), University College London (UCL), London, UK

4. Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China

5. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Provinces

the ESRC under JPI Urban Europe/NSFC

the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme

the Basic Research Program of Shenzhen Science and Technology Innovation Committee

Publisher

Informa UK Limited

Subject

Computers in Earth Sciences,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2021.1996212

Reference56 articles.

1. Chatty maps: constructing sound maps of urban areas from social media data

2. Virtual Space

3. Examining the influence of stop level infrastructure and built environment on bus ridership in Montreal

4. Identifying urban spatial structure and urban vibrancy in highly dense cities using georeferenced social media data

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