{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T13:42:55Z","timestamp":1788961375485,"version":"build-2803163510"},"reference-count":216,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Laboratory of High Impact Weather (special), China Meteorological Administration","award":["2024-K-07"],"award-info":[{"award-number":["2024-K-07"]}]},{"award":["2024-K-07"],"award-info":[{"award-number":["2024-K-07"]}],"id":[{"id":"https:\/\/ror.org\/00bx3rb98","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Yunnan Key Laboratory of Intelligent Monitoring of Natural Resources and Spatiotemporal Big Data Governance","award":["202449CE340023"],"award-info":[{"award-number":["202449CE340023"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["4250010078"],"award-info":[{"award-number":["4250010078"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["4250010078"],"award-info":[{"award-number":["4250010078"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Yunnan Fundamental Research Projects","award":["202501CF070152"],"award-info":[{"award-number":["202501CF070152"]}]},{"name":"Yunjindi Research Projects","award":["KKK0202521065"],"award-info":[{"award-number":["KKK0202521065"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Landslides occur frequently under complex and variable global geomorphological and meteorological conditions, posing serious threats to the ecological environment, human life and property. Traditional monitoring approaches are often inefficient and highly susceptible to external conditions, making them inadequate for large-scale rapid deformation monitoring. Owing to its advantages of high precision, wide-area coverage, and all-weather continuous observation, Interferometric Synthetic Aperture Radar (InSAR) technology has been widely applied in landslide monitoring. This paper systematically reviews the development and application of InSAR technologies in landslide monitoring. Classical methods, including Differential InSAR (D-InSAR), Permanent Scatterer InSAR (PS-InSAR), Small Baseline Subset InSAR (SBAS-InSAR), and Distributed Scatterer InSAR (DS-InSAR), as well as derivative techniques such as Quasi-Permanent Scatterer InSAR (QPS-InSAR), Temporarily Coherent Point InSAR (TCP-InSAR), and Multiple Aperture InSAR (MAI), are comprehensively summarized. In addition, recent advances in artificial intelligence (AI) and multi-source data fusion are highlighted. Through comparative analysis of related studies, this paper summarizes the applicability and potential of various methods in landslide monitoring, and reviews the main solutions to challenges, including geometric distortion, decorrelation noise, atmospheric delay, and difficulties in three-dimensional deformation monitoring. Future research directions are also discussed. Overall, InSAR technology has evolved from single-method approaches toward integrated and intelligent frameworks; however, challenges remain in terms of adaptability in complex terrain, data-processing efficiency, and model interpretability. This review provides a technical reference for future landslide-monitoring research.<\/jats:p>","DOI":"10.3390\/s26154667","type":"journal-article","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T09:11:26Z","timestamp":1784797886000},"page":"4667","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["InSAR Techniques for Landslide Study: A Review of Methods, Challenges, and Emerging Trends"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-2408-646X","authenticated-orcid":false,"given":"Hanlu","family":"Zhang","sequence":"first","affiliation":[{"name":"Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650031, China"},{"name":"Yunnan Key Laboratory of Intelligent Monitoring and Spatiotemporal Big Data Governance of Natural Resources, Kunming 650051, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bowen","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of High Impact Weather (Special), Changsha 410073, China"},{"name":"Yunnan Meteorological Observatory, Kunming 650034, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daming","family":"Zhu","sequence":"additional","affiliation":[{"name":"Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650031, China"},{"name":"Yunnan Key Laboratory of Intelligent Monitoring and Spatiotemporal Big Data Governance of Natural Resources, Kunming 650051, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhanfeng","family":"Liu","sequence":"additional","affiliation":[{"name":"Yunnan Key Laboratory of Intelligent Monitoring and Spatiotemporal Big Data Governance of Natural Resources, Kunming 650051, China"},{"name":"Yunnan Institute of Geology and Mineral Surveying and Mapping Co., Ltd., Kunming 650051, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2236-6981","authenticated-orcid":false,"given":"Mengyao","family":"Shi","sequence":"additional","affiliation":[{"name":"Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2161","DOI":"10.5194\/nhess-18-2161-2018","article-title":"Global fatal landslide occurrence from 2004 to 2016","volume":"18","author":"Froude","year":"2018","journal-title":"Nat. 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