{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T22:10:42Z","timestamp":1790115042391,"version":"4.0.1"},"reference-count":39,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,26]],"date-time":"2022-12-26T00:00:00Z","timestamp":1672012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Nature Science Foundation of China","award":["41471333"],"award-info":[{"award-number":["41471333"]}]},{"name":"National Nature Science Foundation of China","award":["42201500"],"award-info":[{"award-number":["42201500"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Understanding intercity mobility patterns is important for future urban planning, in which the intensity of intercity mobility indicates the degree of urban integration development. This study investigates the intercity mobility patterns of the Greater Bay Area (GBA) in China. The proposed workflow starts by analyzing intercity mobility characteristics, proceeds to model the spatial-temporal heterogeneity of intercity mobility structures, and then identifies the intercity mobility patterns. We first conduct a complex network analysis, based on weighted degrees and the PageRank algorithm, to measure intercity mobility characteristics. Next, we calculate the Normalized Levenshtein Distance for Population Mobility Structure (NLPMS) to quantify the differences in intercity mobility structures, and we use the Non-negative Matrix Factorization (NMF) to identify intercity mobility patterns. Our results showed an evident \u2018Core-Periphery\u2019 differentiation characterized by intercity mobility, with Guangzhou and Shenzhen as the two core cities. An obvious daily intercity commuting pattern was found between Guangzhou and Foshan, and between Shenzhen and Dongguan cities at working time. This pattern, however, changes during the holidays. This is because people move from the core cities to peripheral cities at the beginning of holidays and return at the end of holidays. This study concludes that Guangzhou and Foshan have formed a relatively stable intercity mobility pattern, and the Shenzhen\u2013Dongguan\u2013Huizhou metropolitan area has been gradually formed.<\/jats:p>","DOI":"10.3390\/ijgi12010005","type":"journal-article","created":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T04:58:01Z","timestamp":1672117081000},"page":"5","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Characterizing Intercity Mobility Patterns for the Greater Bay Area in China"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9218-741X","authenticated-orcid":false,"given":"Yanzhong","family":"Yin","sequence":"first","affiliation":[{"name":"Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350108, China"},{"name":"National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou 350108, China"},{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4081-5293","authenticated-orcid":false,"given":"Qunyong","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350108, China"},{"name":"National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou 350108, China"},{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9083-0475","authenticated-orcid":false,"given":"Mengmeng","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350108, China"},{"name":"National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou 350108, China"},{"name":"The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102801","DOI":"10.1016\/j.cities.2020.102801","article-title":"The spatial integration and coordinated industrial development of urban agglomerations in the Yangtze River Economic Belt, China","volume":"104","author":"Liu","year":"2020","journal-title":"Cities"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.scitotenv.2014.02.073","article-title":"Internal migration and urbanization in China: Impacts on population exposure to household air pollution (2000\u20132010)","volume":"481","author":"Aunan","year":"2014","journal-title":"Sci. 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