期刊
GEOMORPHOLOGY
卷 356, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.geomorph.2020.107084
关键词
Landslide susceptibility; Data heterogeneity; Slope units; Positional inaccuracy
资金
- Belgium Science Policy (BELSPO) through the AfReSlide project in the BRAIN program [BR/121/A2/AfReSlide]
- Research Foundation Flanders (FWO)
- VLIR South-Initiative [ZEIN2013Z145, UG2017SIN208A105]
- Moon University
Regional landslide inventories are often prepared by several different experts, using a variety of data sources. This can result in a combination of polygon and point landslide data, characterized by different meanings, uncertainties and levels of reliability. The propagation of uncertainties due to such heterogeneous data is a relevant issue in statistical landslide susceptibility zonation at supra-local scale. In the inhabited highlands of the Rwenzori Mountains, we compare different approaches and mapping units to provide a robust methodology for susceptibility mapping using a combination of landslide point and polygon data. First, the effect of the uncertainty related to a point representation of landslides is assessed comparing slope unit-based and pixel-based analyses, using digital elevation models with different resolutions. Secondly, with regard to landslide polygon inventories, we compare the use of thresholds versus a presence/absence of the depletion centroid or a randomly selected point in the landslide polygon in order to identify slope units with landslides. Based on these results, we prepare regional slope unit-based susceptibility maps using a logistic regression model calibrated with the landslide polygon inventory and validated with the point inventory. Although pixel-based-mapping remains the most common approach for statistical landslide susceptibility zonation, our analysis clearly favours the use of slope units as a powerful tool to prepare regional susceptibility maps and, in particular, to exploit heterogeneous information in a consistent way. (C) 2020 Elsevier B.V. All rights reserved.
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