Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/117002
DC FieldValueLanguage
dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorGu, X-
dc.creatorYu, M-
dc.creatorLiu, X-
dc.date.accessioned2026-01-21T03:54:46Z-
dc.date.available2026-01-21T03:54:46Z-
dc.identifier.issn2096-4471-
dc.identifier.urihttp://hdl.handle.net/10397/117002-
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.rights© 2025 The Author(s). Published by Taylor & Francis Group and Science Press on behalf of the International Society for Digital Earth, supported by the International Research Center of Big Data for Sustainable Development Goals.en_US
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.en_US
dc.rightsThe following publication Gu, X., Yu, M., & Liu, X. (2025). A city-level dataset of population subcenters in Chinese cities for urban polycentric detection (2001–2021). Big Earth Data, 9(4), 1210-1225 is available at https://doi.org/10.1080/20964471.2025.2560164.en_US
dc.subjectPolycentric structureen_US
dc.subjectPopulation centeren_US
dc.subjectUrban planningen_US
dc.subjectUrban structureen_US
dc.titleA city-level dataset of population subcenters in Chinese cities for urban polycentric detection (2001–2021)en_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1210-
dc.identifier.epage1225-
dc.identifier.volume9-
dc.identifier.issue4-
dc.identifier.doi10.1080/20964471.2025.2560164-
dcterms.abstractUrban areas across the globe are experiencing a shift towards polycentric development, characterized by the emergence of multiple subcenters within cities that can respectively function as economic, social, and residential hubs. In response to this trend, we generate a city-level dataset of population subcenters covering 336 cities in China to serve dynamic urban polycentric detection from 2001 to 2021 though analyzing Landscan data. Our dataset has been validated by diverse socio-economic factors, demonstrating that it can provide a relatively accurate depiction of urban structural changes. It comprehensively captures the evolution of urban polycentric structures within China’s rapidly transforming cities, offering detailed insights into the formation and dynamics of population subcenters over two decades. These findings can facilitate policymakers with evidence-based tools to optimize infrastructure and services distributions, thereby fostering efficient urban environments. Moreover, the dataset supports advanced spatiotemporal analysis and modeling, which are essential for understanding urban sustainable development. The dataset is beneficial to explore patterns of urban growth, assessing policy impacts, and developing predictive models for urban structure evolution. All data, figures and relevant results are publicly available on Zenodo: https://doi.org/10.5281/zenodo.14279505.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationBig Earth data, 2025, v. 9, no. 4, p. 1210-1225-
dcterms.isPartOfBig Earth data-
dcterms.issued2025-
dc.identifier.scopus2-s2.0-105016834783-
dc.identifier.eissn2574-5417-
dc.description.validate202601 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis work is funded by The Hong Kong Polytechnic University (UGC) [1-WZ43].en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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