Rocky Mountain Research Station Logo USDA Forest Service
Rocky Mountain Research Station
Forestry Sciences Laboratory - Moscow, Idaho
Moscow Personnel  |  Site Index  |  Site Map  |  Moscow Home
Project Information  |  Modeling Software  |  Library  |  Project Photos  |  Offsite Links  |  Eng. Home

Soil & Water
Engineering Publications


Project Leader:
William J. Elliot
email Bill

Contact Webmaster
email webmaster

Database updated
859 days ago

Spatial prediction of landslide hazard using discriminant analysis and GIS

Gorsevski P.V.; Gessler, P.E.; Foltz, R.B. 2000. Spatial Prediction of Landslide Hazard using Discriminant Analysis and GIS. GIS in the Rockies 2000 Conference and Workshop: Applications for the 21st Century, September 25-27, 2000, Denver, Colorado. 10 p.

Keywords: Landslides, Landslide Hazard, Slope Stability, Geographic Information System, Spatial Prediction, Multivariate Models, Discriminant Analysis

Links: pdf PDF [294K USFS]

Abstract: Environmental attributes relevant for spatial prediction of landslides triggered by rain and snowmelt events were derived from a digital elevation model (DEM). Those data in conjunction with statistics and a 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.

Moscow FSL publication no. 2000k