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
25 days ago

Spatial prediction of landslide hazard using logistic regression and ROC analysis

Gorsevski, P.V.; Gessler, P.E.; Foltz, R.B.; Elliot, W.J. 2006. Spatial Prediction of Landslide Hazard Using Logistic Regression and ROC Analysis. Transactions in GIS 10(3):395-415.

Keywords: landslide

Links:

Available to purchase: PDF

Abstract: An empirical modeling of road related and non-road related landslide hazard for a large geographical area using logistic regression in tandem with signal detection theory is presented. This modeling was developed using geographic information system (GIS) and remote sensing data, and was implemented on the Clearwater National Forest in central Idaho. The approach is based on explicit and quantitative environmental correlations between observed landslide occurrences, climate, parent material, and environmental attributes while the receiver operating characteristic (ROC) curves are used as a measure of performance of a predictive rule. The modeling results suggest that development of two independent models for road related and non-road related landslide hazard was necessary because spatial prediction and predictor variables were different for these models. The probabilistic models of landslide potential may be used as a decision support tool in forest planning involving the maintenance, obliteration or development of new forest roads in steep mountainous terrain.

Moscow FSL publication no. 2006t