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| Titel |
Evaluation of a preliminary satellite-based landslide hazard algorithm using global landslide inventories |
| VerfasserIn |
D. B. Kirschbaum, R. Adler, Y. Hong, A. Lerner-Lam |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 9, no. 3 ; Nr. 9, no. 3 (2009-05-06), S.673-686 |
| Datensatznummer |
250006777
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| Publikation (Nr.) |
 copernicus.org/nhess-9-673-2009.pdf |
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| Zusammenfassung |
| Most landslide hazard assessment algorithms in common use are applied to
small regions, where high-resolution, in situ, observables are available. A
preliminary global landslide hazard algorithm has been developed to estimate
areas of potential landslide occurrence in near real-time by combining a
calculation of landslide susceptibility with satellite derived rainfall
estimates to forecast areas with increased potential for landslide
conditions. This paper presents a stochastic methodology to compare this
new, landslide hazard algorithm for rainfall-triggered landslides with a
newly available inventory of global landslide events, in order to determine
the predictive skill and limitations of such a global estimation technique.
Additionally, we test the sensitivity of the global algorithm to its input
observables, including precipitation, topography, land cover and soil
variables. Our analysis indicates that the current algorithm is limited by
issues related to both the surface-based susceptibility map and the temporal
resolution of rainfall information, but shows skill in determining general
geographic and seasonal distributions of landslides. We find that the global
susceptibility model has inadequate performance in certain locations, due to
improper weighting of surface observables in the susceptibility map. This
suggests that the relative contributions of topographic slope and soil
conditions to landslide susceptibility must be considered regionally. The
current, initial forecast system, although showing some overall skill, must
be improved considerably if it is to be used for hazard warning or detailed
studies. Surface and remote sensing observations at higher spatial
resolution, together with improved landslide event catalogues, are required
if global landslide hazard forecasts are to become an operational reality. |
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