{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T06:06:08Z","timestamp":1778825168159,"version":"3.51.4"},"reference-count":43,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2020,8,3]],"date-time":"2020-08-03T00:00:00Z","timestamp":1596412800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Basic Research Program of China (973 Program)","award":["2016YFC0501604-05"],"award-info":[{"award-number":["2016YFC0501604-05"]}]},{"name":"National Basic Research Program of China (973 Program)","award":["2018YFB0505501"],"award-info":[{"award-number":["2018YFB0505501"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Massive landslides over large regions can be triggered by heavy rainfalls or major seismic events. Mapping regional landslides quickly is important for disaster mitigation. In recent years, deep learning methods have been successfully applied in many fields, including landslide automatic identification. In this work, we proposed a deep learning approach, the ResU-Net, to map regional landslides automatically. This method and a baseline model (U-Net) were collectively tested in Tianshui city, Gansu province, where a heavy rainfall triggered more than 10,000 landslides in July 2013. All models were performed on a 3-band (near infrared, red, and green) GeoEye-1 image with a spatial resolution of 0.5 m. At such a fine spatial resolution, the study area is spatially heterogeneous. The tested study area is 128 km2, 80% of which was used to train models and the remaining 20% was used to validate accuracy of the models. This proposed ResU-Net achieved higher accuracy than the baseline U-Net model in this mountain region, where F1 improved by 0.09. Compared with the U-Net model, this proposed model (ResU-Net) performs better in discriminating landslides from bare floodplains along river valleys and unplanted terraces. By incorporating environmental information, this ResU-Net may also be applied to other landslide mapping, such as landslide susceptibility and hazard assessment.<\/jats:p>","DOI":"10.3390\/rs12152487","type":"journal-article","created":{"date-parts":[[2020,8,3]],"date-time":"2020-08-03T07:45:57Z","timestamp":1596440757000},"page":"2487","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":120,"title":["Automatic Mapping of Landslides by the ResU-Net"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8439-4339","authenticated-orcid":false,"given":"Wenwen","family":"Qi","sequence":"first","affiliation":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China"},{"name":"Beijing Twenty-First Century Science and Technology Development Co. Ltd., Beijing 100096, China"}]},{"given":"Mengfei","family":"Wei","sequence":"additional","affiliation":[{"name":"Twenty-First Century Aerospace Technology Co., Ltd., Beijing 100096, China"}]},{"given":"Wentao","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3956-4925","authenticated-orcid":false,"given":"Chong","family":"Xu","sequence":"additional","affiliation":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China"}]},{"given":"Chao","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s11069-009-9392-1","article-title":"The Wenchuan Earthquake (May 12, 2008), Sichuan Province, China, and resulting geohazards","volume":"56","author":"Cui","year":"2011","journal-title":"Nat. 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