{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T18:28:32Z","timestamp":1776104912203,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2023,9,2]],"date-time":"2023-09-02T00:00:00Z","timestamp":1693612800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41971379"],"award-info":[{"award-number":["41971379"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2018YFB2100703"],"award-info":[{"award-number":["2018YFB2100703"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Program of China","award":["41971379"],"award-info":[{"award-number":["41971379"]}]},{"name":"National Key Research and Development Program of China","award":["2018YFB2100703"],"award-info":[{"award-number":["2018YFB2100703"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rapid urban expansion caused by vigorous urban population growth brought up various socioeconomic and eco-environmental problems, which have important ramifications for sustainable development across the world. Along with the accelerated urbanization process, accurate and realistic prediction of urban expansion is of great importance to optimize urban planning and urban development. This study proposed a new hybrid model, which combined the urban scaling law (USL) with the ANN-CA model to predict urban expansion. To employ urban scaling law in the model, we innovatively calculated the law exponent at a single-city scale. Based on USL, we estimated urban land demand in the future by panel data regression. Finally, we added the area constraint and ecological constraint into the ANN-CA model to simulate urban expansion spatially. This frame of urban expansion has been successfully applied in Shenzhen, of which the urban land area would increase from 816.45 km2 in 2020 to 842.48 km2 in 2025. By comparing this model with the traditional prediction method, we proved its effectiveness and accuracy. Besides, we found that the scaling exponent can reflect urbanization level and distinguish overconstructed cities.<\/jats:p>","DOI":"10.3390\/rs15174326","type":"journal-article","created":{"date-parts":[[2023,9,4]],"date-time":"2023-09-04T02:43:20Z","timestamp":1693795400000},"page":"4326","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Novel Approach to Predicting Urban Expansion by the Urban Scaling Law at a Single-City Scale"],"prefix":"10.3390","volume":"15","author":[{"given":"Haipeng","family":"Ye","sequence":"first","affiliation":[{"name":"Institute of Transportation Engineering and Geomatics, Department of Civil Engineering, Tsinghua University, Beijing 100084, China"},{"name":"3S Center, Tsinghua University, Beijing 100084, China"}]},{"given":"Zhuofan","family":"Zheng","sequence":"additional","affiliation":[{"name":"Institute of Transportation Engineering and Geomatics, Department of Civil Engineering, Tsinghua University, Beijing 100084, China"},{"name":"3S Center, Tsinghua University, Beijing 100084, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8237-3780","authenticated-orcid":false,"given":"Xintong","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Transportation Engineering and Geomatics, Department of Civil Engineering, Tsinghua University, Beijing 100084, China"},{"name":"3S Center, Tsinghua University, Beijing 100084, China"}]},{"given":"Shu","family":"Wang","sequence":"additional","affiliation":[{"name":"Chongqing Geomatics and Remote Sensing Center, Chongqing 401147, China"}]},{"given":"Hongrui","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Transportation Engineering and Geomatics, Department of Civil Engineering, Tsinghua University, Beijing 100084, China"},{"name":"3S Center, Tsinghua University, Beijing 100084, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,2]]},"reference":[{"key":"ref_1","unstructured":"United Nations, Department of Economic and Social Affairs, Population Division (2019). 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