Assessing urban livability in Shanghai through an open source data-driven approach

Urban livability has become a major policy and practice priority in many parts of the world. However, its attainment remains challenging in many cities of developing and emerging economies. The lack of data with appropriate quality, coverage, and spatial and temporal resolution often complicates bot...

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Bibliographic Details
Published in:npj Urban Sustainability Vol. 4; no. 1; pp. 7 - 14
Main Authors: Long, Yin, Wu, Yi, Huang, Liqiao, Aleksejeva, Jelena, Iossifova, Deljana, Dong, Nannan, Gasparatos, Alexandros
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 26.02.2024
Springer Nature B.V
Nature Portfolio
Subjects:
4014/4005
706/2808
Cities
Datasets
Earth and Environmental Science
Environment
Living conditions
Open data
Population density
Population distribution
Prices
Quality of life
Sustainable Development
Temporal resolution
towns
Transportation networks
Urban areas
Urban Ecology
Urban Geography
Urban planning
Urbanism
Urbanism (inc. megacities
Urbanization
China
ISSN:2661-8001, 2661-8001
Online Access:Get full text
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Summary:Urban livability has become a major policy and practice priority in many parts of the world. However, its attainment remains challenging in many cities of developing and emerging economies. The lack of data with appropriate quality, coverage, and spatial and temporal resolution often complicates both the assessment of livability in such cities and the identification of priority areas for improvement. Here we develop a framework to mobilize and synthesize open-source data to analyze spatially urban livability patterns in Shanghai. The framework brings together diverse types of open-source data including housing characteristics, population distribution, transportation networks, and points of interest to identify city areas with low livability, and thus priority areas for improvement. Such findings can provide a comprehensive overview of the residential living conditions in Shanghai, as well as useful information to urban planners and decision-makers. Furthermore, subject to data availability, the proposed method has the potential for application in other cities.
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ISSN:2661-8001
2661-8001
DOI:10.1038/s42949-024-00146-z