A previously studied spatial database for representing landslide susceptibility is reanalyzed to bring out aspects of relative quality and uncertainty of the resulting prediction pattern. Using the empirical likelihood ratio function, a processing strategy, based on cross-validation, target pattern and prediction rates, is used to asses the suitability of the database for prediction modeling. Sharing of databases is seen as fundamental for discussing and understanding prediction modeling.
Uncertainty of class membership in spatial prediction modeling: follow-up study to an application to complex landslides
Sterlacchini S;Cavallin A;
2011
Abstract
A previously studied spatial database for representing landslide susceptibility is reanalyzed to bring out aspects of relative quality and uncertainty of the resulting prediction pattern. Using the empirical likelihood ratio function, a processing strategy, based on cross-validation, target pattern and prediction rates, is used to asses the suitability of the database for prediction modeling. Sharing of databases is seen as fundamental for discussing and understanding prediction modeling.File in questo prodotto:
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