{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T20:04:24Z","timestamp":1772741064642,"version":"3.50.1"},"reference-count":49,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T00:00:00Z","timestamp":1631059200000},"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":["41941019, 42074040, 41731066, 41790445"],"award-info":[{"award-number":["41941019, 42074040, 41731066, 41790445"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the National Key R&amp;D Program of China","award":["2020YFC1512001, 2019YFC1509800"],"award-info":[{"award-number":["2020YFC1512001, 2019YFC1509800"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Construction of the 998.64-km Linzhi\u2013Ya\u2019an section of the Sichuan\u2013Tibet Railway has been influenced by landslide disasters, threatening the safety of Sichuan\u2013Tibet railway projects. Landslide identification and deformation analysis in this area are urgently needed. In this context, it was the first time that 164 advanced land-observing satellite-2 (ALOS-2) phased array type L-band synthetic aperture radar-2 (PALSAR-2) images were collected to detect landslide disasters along the entire Linzhi\u2013Ya\u2019an section. Interferogram stacking and small baseline interferometry methods were used to derive the deformation rate and time-series deformation from 2014\u20132020. After that, the hot spot analysis method was introduced to conduct spatial clustering analysis of the annual deformation rate, and the effective deformation area was quickly extracted. Finally, 517 landslide disasters along the Linzhi\u2013Ya\u2019an route were detected by integrating observed deformation, Google Earth optical images, and external geological data. The main factors controlling the spatial landslide distribution were analyzed. In the vertical direction, the spatial landslide distribution was mainly concentrated in the elevation range of 3000\u20135000 m, the slope range of 10\u201340\u00b0, and the aspect of northeast and east. In the horizontal direction, landslides were concentrated near rivers, and were also closely related to earthquake-prone areas, fault zones, and high-precipitation areas. In short, rainfall, freeze\u2013thaw weathering, seismic activity, and fault zones are the main factors inducing landslides along this route. This research provides scientific support for the construction and operation of the Linzhi\u2013Ya\u2019an section of the Sichuan\u2013Tibet Railway.<\/jats:p>","DOI":"10.3390\/rs13183566","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T10:12:03Z","timestamp":1631095923000},"page":"3566","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":59,"title":["Landslide Detection in the Linzhi\u2013Ya\u2019an Section along the Sichuan\u2013Tibet Railway Based on InSAR and Hot Spot Analysis Methods"],"prefix":"10.3390","volume":"13","author":[{"given":"Jinmin","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Geological Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"},{"name":"Big Data Center for Geosciences and Satellites, Chang\u2019an University, Xi\u2019an 710054, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6034-3062","authenticated-orcid":false,"given":"Wu","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Geological Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"},{"name":"Big Data Center for Geosciences and Satellites, Chang\u2019an University, Xi\u2019an 710054, China"},{"name":"Key Laboratory of Western China\u2019s Mineral Resources and Geological Engineering, Ministry of Education, Xi\u2019an 710054, China"}]},{"given":"Yiqing","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Geological Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"},{"name":"Big Data Center for Geosciences and Satellites, Chang\u2019an University, Xi\u2019an 710054, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8054-7449","authenticated-orcid":false,"given":"Zhenhong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geological Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"},{"name":"Big Data Center for Geosciences and Satellites, Chang\u2019an University, Xi\u2019an 710054, China"},{"name":"Key Laboratory of Western China\u2019s Mineral Resources and Geological Engineering, Ministry of Education, Xi\u2019an 710054, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,8]]},"reference":[{"key":"ref_1","first-page":"2377","article-title":"Challenges to engineering geology of Sichuan\u2014Tibet railway","volume":"39","author":"Peng","year":"2020","journal-title":"Chin. 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