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Spatial prediction of landslide hazard using discriminant analysis and GISAuthor(s): Peter V. Gorsevski; Paul Gessler; Randy B. Foltz
Source: In: GIS in the Rockies 2000 Conference and Workshop: applications for the 21st Century, Denver, Colorado, September 25 - 27, 2000.
Publication Series: Miscellaneous Publication
PDF: View PDF (294 KB)
DescriptionEnvironmental attributes relevant for spatial prediction of landslides triggered by rain and snowmelt events were derived from digital elevation model (DEM). Those data in conjunction with statistics and geographic information system (GIS) provided a detailed basis for spatial prediction of landslide hazard. The spatial prediction of landslide hazard in this paper is based on discriminant analysis. Discriminant analysis is a multivariate technique that can be used to build rules that can classify elements or observations successfully between stable and unstable areas. The discriminant rule would show how to take into account the relative risks of making errors of misclassification. Those general rules allow managers to consider that errors in one direction may be much more costly than errors in the other direction.
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CitationGorsevski, Peter V.; Gessler, Paul; Foltz, Randy B. 2000. Spatial prediction of landslide hazard using discriminant analysis and GIS. In: GIS in the Rockies 2000 Conference and Workshop: applications for the 21st Century, Denver, Colorado, September 25 - 27, 2000.
Keywordslandslides, landslide hazard, slope stability, geographic information system, spatial prediction, multivariate models, discriminant analysis
- Statistical modeling of landslide hazard using GIS
- Predicting landslides in clearcut patches
- Spatially explicit shallow landslide susceptibility mapping over large areas
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