{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T02:53:15Z","timestamp":1777085595726,"version":"3.51.4"},"reference-count":36,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T00:00:00Z","timestamp":1656288000000},"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":["42174039"],"award-info":[{"award-number":["42174039"]}],"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":["2021JJ30807"],"award-info":[{"award-number":["2021JJ30807"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Hunan Province","award":["42174039"],"award-info":[{"award-number":["42174039"]}]},{"name":"Natural Science Foundation of Hunan Province","award":["2021JJ30807"],"award-info":[{"award-number":["2021JJ30807"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Many coastal cities reclaim land from the sea to meet the rapidly growing demand for land caused by population growth and economic development. Settlement in reclaimed land may delay construction and even damage infrastructures, so accurately predicting the settlement over reclaimed areas is important. However, the limited settlement observation and ambiguous final settlement estimation affect accurate settlement prediction in traditional methods. This study proposes a new strategy to solve these problems by using the Multitemporal Interferometric Synthetic Aperture Radar (MT-InSAR) method and takes the Xiamen Xiang\u2019an International Airport, built on reclaimed land, as an example. The MT-InSAR is adopted to process the Sentinel-1 images to obtain the settlement history of the study area. The results show that settlement mainly occurs in the reclaimed areas, with the maximum average settlement rate exceeding 40 mm\/y. We use the statistical properties of curve fitting to choose the best curve model from several candidate curve models to predict the settlement time series. The Asaoka method is used to identify the critical state between settlement and stability. We predict the consolidation time of the whole study area and reveal that the deformation rate is positively correlated with the consolidation time. The maximum remaining settlement time is over ten years since 24 December 2019. Therefore, manual compaction operations can be carried out to speed up settlement in the areas that need a long time to consolidate. The proposed method can be used to predict the settlement of similar reclaimed areas, and the predicted results can provide a reference for engineering construction.<\/jats:p>","DOI":"10.3390\/rs14133081","type":"journal-article","created":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T00:07:02Z","timestamp":1656374822000},"page":"3081","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Settlement Prediction of Reclaimed Coastal Airports with InSAR Observation: A Case Study of the Xiamen Xiang\u2019an International Airport, China"],"prefix":"10.3390","volume":"14","author":[{"given":"Zhiqiang","family":"Xiong","sequence":"first","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kailiang","family":"Deng","sequence":"additional","affiliation":[{"name":"Naval Institute of Hydrographic Surveying and Charting, Tianjin 300061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangcai","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Miao","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaifeng","family":"Li","sequence":"additional","affiliation":[{"name":"Naval Institute of Hydrographic Surveying and Charting, Tianjin 300061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chulu","family":"He","sequence":"additional","affiliation":[{"name":"Fujian Provincial Institute of Land Surveying and Mapping, Xiamen 361006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanrong","family":"He","sequence":"additional","affiliation":[{"name":"Big Data Institute of Digital Natural Disaster Monitoring in Fujian, Xiamen University of Technology, Xiamen 361024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yu, Q., Yan, X., Wang, Q., Yang, T., Lu, W., Yao, M., Dong, J., Zhan, J., Huang, X., and Niu, C. 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