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Modeling Accumulated Volume of Landslides Using Remote Sensing and DTM Data
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
Hunan Province Engineering Laboratory of Geo-spatial Information, Hunan University of Science and Technology, Xiangtan 411201, China
National Earthquake Response Support Service, China Earthquake Administration, Beijing 100049, China
* Author to whom correspondence should be addressed.
Received: 21 November 2013; in revised form: 30 December 2013 / Accepted: 24 January 2014 / Published: 19 February 2014
Abstract: 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 “height adaptor”, 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.
Keywords: landslide; volume calculation; mass balance; remote sensing; digital terrain model (DTM); Wenchuan
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MDPI and ACS Style
Chen, Z.; Zhang, B.; Han, Y.; Zuo, Z.; Zhang, X. Modeling Accumulated Volume of Landslides Using Remote Sensing and DTM Data. Remote Sens. 2014, 6, 1514-1537.
Chen Z, Zhang B, Han Y, Zuo Z, Zhang X. Modeling Accumulated Volume of Landslides Using Remote Sensing and DTM Data. Remote Sensing. 2014; 6(2):1514-1537.
Chen, Zhengchao; Zhang, Bing; Han, Yongshun; Zuo, Zhengli; Zhang, Xiaoyong. 2014. "Modeling Accumulated Volume of Landslides Using Remote Sensing and DTM Data." Remote Sens. 6, no. 2: 1514-1537.