{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T05:03:32Z","timestamp":1772427812562,"version":"3.50.1"},"reference-count":58,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2017,5,6]],"date-time":"2017-05-06T00:00:00Z","timestamp":1494028800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rapid urbanization has resulted in great changes in rural landscapes globally. Using remote sensing data to quantify the distribution of rural settlements and their changes has received increasing attention in the past three decades, but remains a challenge. Previous studies mostly focused on the residential changes within a grid or administrative boundary, but not at the individual village level. This paper presents a new change detection approach for rural residential settlements, which can identify different types of rural settlement changes at the individual village level by integrating remote sensing and Geographic Information System (GIS) analyses. Using multi-temporal Landsat TM image data, this approach classifies villages into five types: \u201cno change\u201d, \u201ctotally lost\u201d, \u201cshrinking\u201d, \u201cexpanding\u201d, and \u201cmerged\u201d, in contrast to the commonly used \u201cincrease\u201d and \u201cdecrease\u201d. This approach was tested in the Beijing metropolitan area from 1984 to 2010. Additionally, the drivers of such changes were investigated using multinomial logistic regression models. The results revealed that: (1) 36% of the villages were lost, but the total area of developed lands in existing villages increased by 34%; (2) Changes were dominated by the type of \u2018expansion\u2019 in 1984\u20131990 (accounted for 43.42%) and 1990\u20132000 (56.21%). However, from 2000 to 2010, 49.73% of the villages remained unchanged; (3) Both topographical factors and distance factors had significant effects on whether the villages changed or not, but their impacts changed through time. The topographical driving factors showed decreasing effects on the loss of rural settlements, while distance factors had increasing impacts on settlement expansion and merging. This approach provides a useful tool for better understanding the changes in rural residential settlements and their associations with urbanization.<\/jats:p>","DOI":"10.3390\/rs9050448","type":"journal-article","created":{"date-parts":[[2017,5,8]],"date-time":"2017-05-08T11:45:16Z","timestamp":1494243916000},"page":"448","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Quantifying Changes of Villages in the Urbanizing Beijing Metropolitan Region: Integrating Remote Sensing and GIS Analysis"],"prefix":"10.3390","volume":"9","author":[{"given":"Kun","family":"Wang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Weiqi","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Kaipeng","family":"Xu","sequence":"additional","affiliation":[{"name":"Chinese Academy for Environmental Planning, Beijing 100012, China"}]},{"given":"Hanmei","family":"Liang","sequence":"additional","affiliation":[{"name":"Beijing Institute of Surveying and Mapping, Beijing 100038, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7123-4267","authenticated-orcid":false,"given":"Wenjuan","family":"Yu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Weifeng","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,5,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.landurbplan.2005.02.004","article-title":"Rates and drivers of rural residential development in the Greater Yellowstone","volume":"77","author":"Gude","year":"2006","journal-title":"Landsc. 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