Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/90746
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorSun, Z-
dc.creatorChen, X-
dc.creatorXing, H-
dc.creatorMa, H-
dc.creatorMeng, Y-
dc.date.accessioned2021-09-03T02:33:30Z-
dc.date.available2021-09-03T02:33:30Z-
dc.identifier.urihttp://hdl.handle.net/10397/90746-
dc.language.isoenen_US
dc.publisherPublic Library of Scienceen_US
dc.rights© 2020 Sun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.rightsThe following publication Sun Z, Chen X, Xing H, Ma H, Meng Y (2020) Regional differences in socioeconomic trends: The spatiotemporal evolution from individual cities to a megacity region over a long time series. PLoS ONE 15(12): e0244084 is available at https://doi.org/10.1371/journal.pone.0244084en_US
dc.titleRegional differences in socioeconomic trends : the spatiotemporal evolution from individual cities to a megacity region over a long time seriesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume15-
dc.identifier.issue12-
dc.identifier.doi10.1371/journal.pone.0244084-
dcterms.abstractRegional differences in socioeconomic factors are important for assessing the regional development of an area. While much research has focused on the overall patterns of regional differences within independent cities and areas, the hierarchical spatiotemporal structures of megacity regions have seldom been discussed. To fill this gap, this paper investigates the multilevel regional differences within megacity regions. Employing GDP, population and total retail sales as socioeconomic indicators, the spatiotemporal patterns of socioeconomic trends are identified. A hierarchical clustering approach that utilizes socioeconomic similarities is proposed for the identification of the spatiotemporal patterns of individual cities. At the megacity regional level, gravity centers and pathways are constructed to evaluate spatial imbalances and temporal change intensities. Taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as its study area, this research produces results that show diverse spatiotemporal patterns among the individual cities, revealing high/low starting point and high/low growth rate modes in terms of city interactions. From the perspective of the entire GBA, the spatial imbalance of GDP is the highest of the factors, followed by the spatial imbalance of the total retail sales of the region and, finally, by that of its population. Total retail sales exhibit the highest level of temporal change intensity, followed by GDP and population. In terms of the contribution of the various cities to the overall regional changes, Guangzhou, Shenzhen and Hong Kong dominate the spatiotemporal changes in the gravity centers, while Foshan and Dongguan show significant potential to contribute to these socioeconomic patterns. These results provide effective guidance for the sustainable development of megacity regions.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationPLoS one, 21 Dec. 2020, v. 15, no. 12, e0244084-
dcterms.isPartOfPLoS one-
dcterms.issued2020-12-
dc.identifier.scopus2-s2.0-85098928002-
dc.identifier.pmid33347454-
dc.identifier.eissn1932-6203-
dc.identifier.artne0244084-
dc.description.validate202109 bcvc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
journal.pone.0244084.pdf2.08 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

110
Last Week
4
Last month
Citations as of Nov 10, 2025

Downloads

43
Citations as of Nov 10, 2025

SCOPUSTM   
Citations

8
Citations as of Dec 19, 2025

WEB OF SCIENCETM
Citations

6
Citations as of Dec 18, 2025

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.