{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T21:31:46Z","timestamp":1781299906286,"version":"3.54.1"},"reference-count":42,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["42101345"],"award-info":[{"award-number":["42101345"]}]},{"name":"National Natural Science Foundation of China","award":["2021NDQN39"],"award-info":[{"award-number":["2021NDQN39"]}]},{"name":"Chongqing Social Science Planning Project","award":["42101345"],"award-info":[{"award-number":["42101345"]}]},{"name":"Chongqing Social Science Planning Project","award":["2021NDQN39"],"award-info":[{"award-number":["2021NDQN39"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The regional disparity of urban expansion varies significantly in China\u2019s different regions, hindering sustainable socioeconomic development. However, most studies to date have focused on a single aspect of urban expansion, e.g., urban spatial expansion (USS) disparity. This study attempts to define urban expansion from USS and urban socioeconomic expansion (USE) based on nighttime light remotely sensed (NTL) data and urban land datasets. Then, taking China\u2019s 241 prefecture-level cities within different provinces as experimental subjects, the Dagum Gini (DG) coefficient and stochastic convergence test are employed to assess the disparity of urban expansion from two different dimensions. The results show that, on the national scale, the regional disparity of USS is always greater than that of USE and has a converging trend. Additionally, regional disparity is the main factor causing the difference between USS and USE, with average contribution rates of 55% and 45%, respectively. The average difference between USS and USE in the eastern region (ER) is greater than 10%, while it is the lowest in the northeastern region (NER) and shows a significant expansion trend in performance convergence with a regression coefficient of 0.0022, followed by the central (CR), eastern, and western (WR) regions. Through the panel unit root test, we found that urban expansion in China in terms of USS and USE has internal random convergence in certain regions under the premise of global random divergence, and there may be differentiation and formation of one or more convergence clubs in the future. Using this novel perspective to define urban expansion, this study quantifies the contributions of USS and USE to regional disparity and provides a scientific basis for governments to implement appropriate approaches to sustainable urban development in different regions.<\/jats:p>","DOI":"10.3390\/rs14174348","type":"journal-article","created":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T00:19:01Z","timestamp":1662077941000},"page":"4348","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["The Regional Disparity of Urban Spatial Expansion Is Greater than That of Urban Socioeconomic Expansion in China: A New Perspective from Nighttime Light Remotely Sensed Data and Urban Land Datasets"],"prefix":"10.3390","volume":"14","author":[{"given":"Zhijian","family":"Chang","sequence":"first","affiliation":[{"name":"School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China"},{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shirao","family":"Liu","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yizhen","family":"Wu","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9047-2885","authenticated-orcid":false,"given":"Kaifang","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China"},{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1038\/509158a","article-title":"Society: Realizing China\u2019s urban dream","volume":"509","author":"Bai","year":"2014","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1016\/j.scib.2019.04.024","article-title":"40-Year (1978\u20132017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing","volume":"64","author":"Gong","year":"2019","journal-title":"Sci. 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