Predicting landslides for risk analysis — Spatial models tested by a cross-validation technique |
| |
| Authors: | Chang-Jo Chung Andrea G Fabbri |
| |
| Institution: | aGeological Survey of Canada, Ottawa, Canada;bSPINlab,Vrije Universiteit, Amsterdam, The Netherlands;cDISAT, University of Milano-Bicocca, Milan, Italy |
| |
| Abstract: | A landslide-hazard map is intended to show the location of future slope instability. Most spatial models of the hazard lack reliability tests of the procedures and predictions for estimating the probabilities of future landslides, thus precluding use of the maps for probabilistic risk analysis. To correct this deficiency we propose a systematic procedure comprising two analytical steps: “relative-hazard mapping” and “empirical probability estimation”. A mathematical model first generates a prediction map by dividing an area into “prediction” classes according to the relative likelihood of occurrence of future landslides, conditional by local geomorphic and topographic characteristics. The second stage estimates empirically the probability of landslide occurrence in each prediction class, by applying a cross-validation technique. Cross-validation, a “blind test” here using non-overlapping spatial or temporal subsets of mapped landslides, evaluates accuracy of the prediction and from the resulting statistics estimates occurrence probabilities of future landslides. This quantitative approach, exemplified by several experiments in an area near Lisbon, Portugal, can accommodate any subsequent analysis of landslide risk. |
| |
| Keywords: | Landslide hazard Probability Cross-validation Fuzzy-set membership function Prediction map Spatial modeling Future landslides Risk analysis |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
