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.
Available to purchase: PDF
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