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• W3004421885 endingPage "107084" @default.
• W3004421885 startingPage "107084" @default.
• W3004421885 abstract "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." @default.
• W3004421885 created "2020-02-14" @default.
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• W3004421885 date "2020-05-01" @default.
• W3004421885 modified "2023-10-14" @default.
• W3004421885 title "Regional susceptibility assessments with heterogeneous landslide information: Slope unit- vs. pixel-based approach" @default.
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• W3004421885 doi "https://doi.org/10.1016/j.geomorph.2020.107084" @default.
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