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| Titel |
Rainfall and earthquake-induced landslide susceptibility assessment using GIS and Artificial Neural Network |
| VerfasserIn |
Y. Li, G. Chen, C. Tang, G. Zhou, L. Zheng |
| 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 ; 12, no. 8 ; Nr. 12, no. 8 (2012-08-31), S.2719-2729 |
| Datensatznummer |
250011061
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| Publikation (Nr.) |
 copernicus.org/nhess-12-2719-2012.pdf |
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| Zusammenfassung |
A GIS-based method for the assessment of landslide susceptibility in a
selected area of Qingchuan County in China is proposed by using the
back-propagation Artificial Neural Network model (ANN). Landslide inventory
was derived from field investigation and aerial photo interpretation. 473 landslides occurred before the Wenchuan earthquake (which were thought as
rainfall-induced landslides (RIL) in this study), and 885 earthquake-induced
landslides (EIL) were recorded into the landslide inventory map. To
understand the different impacts of rainfall and earthquake on landslide
occurrence, we first compared the variations between landslide spatial
distribution and conditioning factors. Then, we compared the weight variation
of each conditioning factor derived by adjusting ANN structure and factors
combination respectively. Last, the weight of each factor derived from the
best prediction model was applied to the entire study area to produce
landslide susceptibility maps.
Results show that slope gradient has the highest weight for landslide
susceptibility mapping for both RIL and EIL. The RIL model built with four
different factors (slope gradient, elevation, slope height and distance to
the stream) shows the best success rate of 93%; the EIL model built with
five different factors (slope gradient, elevation, slope height, distance to
the stream and distance to the fault) has the best success rate of 98%.
Furthermore, the EIL data was used to verify the RIL model and the success
rate is 92%; the RIL data was used to verify the EIL model and the
success rate is 53%. |
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