Application of a multi-temporal, LiDAR-derived, digital terrain model in a landslide-volume estimation

Chih Ming Tseng, Ching Weei Lin, Colin P. Stark, Jin Kin Liu, Li Yuan Fei, Yu Chung Hsieh

研究成果: Article同行評審

45 引文 斯高帕斯(Scopus)


Sediments produced by landslides are crucial in the sediment yield of a catchment, debris flow forecasting, and related hazard assessment. On a regional scale, however, it is difficult and time consuming to measure the volumes of such sediment. This paper uses a LiDAR-derived digital terrain model (DTM) taken in 2005 and 2010 (at 2m resolution) to accurately obtain landslide-induced sediment volumes that resulted from a single catastrophic typhoon event in a heavily forested mountainous area of Taiwan. The landslides induced by Typhoon Morakot are mapped by comparison of 25cm resolution aerial photographs taken before and after the typhoon in an 83.6km2 study area. Each landslide volume is calculated by subtraction of the 2005 DTM from the 2010 DTM, and the scaling relationship between landslide area and its volume are further regressed. The relationship between volume and area are also determined for all the disturbed areas (VL=0.452AL1.242) and for the crown areas of the landslides (VL=2.510AL1.206). The uncertainty in estimated volume caused by use of the LiDAR DTMs is discussed, and the error in absolute volume estimation for landslides with an area >105m2 is within 20%. The volume-area relationship obtained in this study is also validated in 11 small to medium-sized catchments located outside the study area, and there is good agreement between the calculation from DTMs and the regression formula. By comparison of debris volumes estimated in this study with previous work, it is found that a wider volume variation exists that is directly proportional to the landslide area, especially under a higher scaling exponent.

頁(從 - 到)1587-1601
期刊Earth Surface Processes and Landforms
出版狀態Published - 2013 10月

All Science Journal Classification (ASJC) codes

  • 地理、規劃與發展
  • 地表過程
  • 地球與行星科學(雜項)


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