{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T22:04:06Z","timestamp":1776377046066,"version":"3.51.2"},"reference-count":54,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2014,2,19]],"date-time":"2014-02-19T00:00:00Z","timestamp":1392768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Landslides, like other natural hazards, such as avalanches, floods, and debris flows, may result in a lot of property damage and human casualties. The volume of landslide deposits is a key parameter for landslide studies and disaster relief. Using remote sensing and digital terrain model (DTM) data, this paper analyzes errors that can occur in calculating landslide volumes using conventional models. To improve existing models, the mechanisms and laws governing the material deposited by landslides are studied and then the mass balance principle and mass balance line are defined. Based on these ideas, a novel and improved model (Mass Balance Model, MBM) is proposed. By using a parameter called the \u201cheight adaptor\u201d, MBM translates the volume calculation into an automatic search for the mass balance line within the scope of the landslide. Due to the use of mass balance constraints and the height adaptor, MBM is much more effective and reliable. A test of MBM was carried out for the case of a typical landslide, triggered by the Wenchuan Earthquake of 12 May 2008.<\/jats:p>","DOI":"10.3390\/rs6021514","type":"journal-article","created":{"date-parts":[[2014,2,19]],"date-time":"2014-02-19T11:10:21Z","timestamp":1392808221000},"page":"1514-1537","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Modeling Accumulated Volume of Landslides Using Remote Sensing and DTM Data"],"prefix":"10.3390","volume":"6","author":[{"given":"Zhengchao","family":"Chen","sequence":"first","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Bing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Yongshun","family":"Han","sequence":"additional","affiliation":[{"name":"Hunan Province Engineering Laboratory of Geo-spatial Information, Hunan University of Science and Technology, Xiangtan 411201, China"}]},{"given":"Zhengli","family":"Zuo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Xiaoyong","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Earthquake Response Support Service, China Earthquake Administration, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2014,2,19]]},"reference":[{"key":"ref_1","unstructured":"Red Cross and Red Crescent Societies (2001). 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