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| Titel |
A dynamic landslide hazard assessment system for Central America and Hispaniola |
| VerfasserIn |
D. B. Kirschbaum, T. Stanley, J. Simmons |
| 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 Sciences ; 15, no. 10 ; Nr. 15, no. 10 (2015-10-09), S.2257-2272 |
| Datensatznummer |
250119716
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| Publikation (Nr.) |
 copernicus.org/nhess-15-2257-2015.pdf |
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| Zusammenfassung |
| Landslides pose a serious threat to life and property in Central America and
the Caribbean Islands. In order to allow regionally coordinated situational
awareness and disaster response, an online decision support system was
created. At its core is a new flexible framework for evaluating potential
landslide activity in near real time: Landslide Hazard Assessment for
Situational Awareness. This framework was implemented in Central America and
the Caribbean by integrating a regional susceptibility map and
satellite-based rainfall estimates into a binary decision tree, considering
both daily and antecedent rainfall. Using a regionally distributed,
percentile-based threshold approach, the model outputs a pixel-by-pixel
nowcast in near real time at a resolution of 30 arcsec to identify
areas of moderate and high landslide hazard. The daily and antecedent
rainfall thresholds in the model are calibrated using a subset of the Global
Landslide Catalog in Central America available for 2007–2013. The model was
then evaluated with data for 2014. Results suggest reasonable model skill
over Central America and poorer performance over Hispaniola due primarily
to the limited availability of calibration and validation data. The
landslide model framework presented here demonstrates the capability to
utilize globally available satellite products for regional landslide hazard
assessment. It also provides a flexible framework to interchange the
individual model components and adjust or calibrate thresholds based on
access to new data and calibration sources. The availability of free
satellite-based near real-time rainfall data allows the creation of similar
models for any study area with a spatiotemporal record of landslide events.
This method may also incorporate other hydrological or atmospheric variables
such as numerical weather forecasts or satellite-based soil moisture
estimates within this decision tree approach for improved hazard analysis. |
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