Analysis of landslide inventories for accurate prediction of debris-flow source areas

被引:117
作者
Blahut, Jan [1 ,2 ]
van Westen, Cees J. [3 ]
Sterlacchini, Simone [2 ]
机构
[1] Univ Milano Bicocca, Dept Environm & Territorial Sci, I-20126 Milan, Italy
[2] CNR, CNR IDPA, Inst Dynam Environm Proc, I-20126 Milan, Italy
[3] ITC, Int Inst Geoinformat Sci & Earth Observat, NL-7500 AA Enschede, Netherlands
关键词
Landslide inventory; Debris flow; Susceptibility analysis; GIS; Italian Alps; SUSCEPTIBILITY ASSESSMENT; HAZARD ASSESSMENT; MODELS; VALIDATION; INFORMATION;
D O I
10.1016/j.geomorph.2010.02.017
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
For the generation of susceptibility maps on medium scales (1:25,000 to 1:50,000) using statistical techniques, a reliable landslide inventory is needed, together with factor maps used as inputs. This paper compares landslide susceptibility maps obtained with the same methodology but using different landslide inventories: the official Italian landslide inventory GeoIFFI for the Lombardy Region and a recently mapped inventory (DF2001). The analysis included four main steps: (i) preparation of debris flow inventories using both random and spatial partitions and factor maps as explanatory variables; (ii) calculation of accountability and reliability indices for a preliminary susceptibility analysis and selection of an appropriate combination of the factor maps for detailed analysis; (iii) evaluation and validation of the obtained susceptibility maps; and (iv) comparison of the results and selection of the final map. The study area is located in the Valtellina Valley in the Central Italian Alps. The analysis identified highly susceptible areas of shallow landslides that may generate debris flows. It was demonstrated that more precisely delimited source areas for landslide-induced debris flows produce better susceptibility maps. However, the improvement of these maps was relatively limited when the inventories were randomly subdivided. Higher improvements were observed after the subdivision of the inventories into three geographical parts with different geomorphological characteristics. Although the modelling showed very similar results if evaluation is made using standard techniques, the spatial pattern of the susceptibility maps was highly variable and dependent on the combination of the factor maps used. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:36 / 51
页数:16
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