{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T18:08:49Z","timestamp":1791569329279,"version":"4.3.4"},"reference-count":39,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2025,1,29]],"date-time":"2025-01-29T00:00:00Z","timestamp":1738108800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Supported by Excellent Graduate Training Program of Shaanxi Normal University","award":["LHRCTS23012"],"award-info":[{"award-number":["LHRCTS23012"]}]},{"DOI":"10.13039\/100014718","name":"Innovative Research Group Project of the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["21BJY086"],"award-info":[{"award-number":["21BJY086"]}],"id":[{"id":"10.13039\/100014718","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>This article compares the population agglomeration characteristics of the Xi\u2019an metropolitan area in western China with those of metropolitan areas in other regions officially approved by the Chinese government. The kernel density estimation method and Markov chain model were used to conduct the study. The results revealed that from 2010 to 2020, the population agglomeration level of the Xi\u2019an metropolitan area showed a trend of first increasing and then decreasing. The absolute gap in the population agglomeration level between cities within the metropolitan area gradually narrowed, and the polarization phenomenon of population agglomeration was not obvious. Compared with metropolitan agglomerations such as Nanjing, Wuhan, Fuzhou, Changsha-Zhuzhou-Xiangtan, Chongqing, and Chengdu, the Xi\u2019an metropolitan agglomeration had a lower population agglomeration level, with a significant gap. Moreover, there was an obvious \u201cclub convergence\u201d phenomenon in the population agglomeration levels of different urban agglomerations. The probability of the population agglomeration level remaining stable was at least 53.85%, indicating that there was a \u201cMatthew effect\u201d in which the rich become richer and the poor become poorer. Through the convergence models of \u03b1 and \u03b2, the analysis suggested that there was no significant \u03b1 convergence between the population agglomeration level of the Xi\u2019an metropolitan agglomeration and that of other metropolitan agglomerations. Instead, there was a significant \u03b2 divergence, indicating that the gap between the Xi\u2019an metropolitan agglomeration\u2019s population agglomeration level and that of other metropolitan agglomerations is gradually widening. An integrated theoretical framework of population agglomeration was constructed from three dimensions: producers, consumers, and social people. An empirical analysis was conducted on the causes of population agglomeration in the Xi\u2019an metropolitan area and other metropolitan areas. The multiple regression results showed that the income level, public consumption expenditure level, education level, comfortable living environment, and educational level were important factors leading to differences in population agglomeration. The geographic detector results showed that factors in the consumer dimension were the main reasons for population agglomeration in metropolitan areas.<\/jats:p>","DOI":"10.1371\/journal.pone.0316385","type":"journal-article","created":{"date-parts":[[2025,1,29]],"date-time":"2025-01-29T18:34:16Z","timestamp":1738175656000},"page":"e0316385","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":4,"title":["Measurement of population agglomeration, dynamic change characteristics, and motivations in metropolitan agglomerations\u2014A case study of the Xi\u2019an metropolitan area"],"prefix":"10.1371","volume":"20","author":[{"given":"Ke","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xu","family":"Bo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wang","family":"Zhaoping","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ran","family":"Du","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Heng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,1,29]]},"reference":[{"issue":"5615","key":"pone.0316385.ref001","doi-asserted-by":"crossref","first-page":"1991","DOI":"10.1126\/science.1080316","article-title":"Demographics. 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