@prefix prodottidellaricerca: . @prefix istituto: . @prefix prodotto: . istituto:CDS028 prodottidellaricerca:prodotto prodotto:ID20165 . @prefix pubblicazioni: . @prefix unitaDiPersonaleInterno: . unitaDiPersonaleInterno:MATRICOLA5850 pubblicazioni:autoreCNRDi prodotto:ID20165 . @prefix modulo: . modulo:ID2586 prodottidellaricerca:prodotto prodotto:ID20165 . @prefix rdf: . prodotto:ID20165 rdf:type prodotto:TIPO1101 . @prefix retescientifica: . prodotto:ID20165 rdf:type retescientifica:ProdottoDellaRicerca . @prefix rdfs: . prodotto:ID20165 rdfs:label "Landslide susceptibility assessment by bivariate methods at large scales: Application to a complex mountainous environment (Articolo in rivista)"@en . @prefix xsd: . prodotto:ID20165 pubblicazioni:anno "2007-01-01T00:00:00+01:00"^^xsd:gYear ; pubblicazioni:doi "10.1016/j.geomorph.2007.02.020"^^xsd:string . @prefix skos: . prodotto:ID20165 skos:altLabel "
Thiery Y., Malet J.-P., Sterlacchini S., Puissant A. & Maquaire O. (2007)
Landslide susceptibility assessment by bivariate methods at large scales: Application to a complex mountainous environment
in Geomorphology (Amst.); Elsevier, Amsterdam (Paesi Bassi)
"^^rdf:HTML ; pubblicazioni:autori "Thiery Y., Malet J.-P., Sterlacchini S., Puissant A. & Maquaire O."^^xsd:string ; pubblicazioni:paginaInizio "38"^^xsd:string ; pubblicazioni:paginaFine "59"^^xsd:string ; pubblicazioni:numeroVolume "92"^^xsd:string . @prefix ns11: . prodotto:ID20165 pubblicazioni:rivista ns11:ID483340 ; pubblicazioni:pagineTotali "22"^^xsd:string ; skos:note "ISI Web of Science (WOS)"^^xsd:string , "Scopus"^^xsd:string ; pubblicazioni:affiliazioni "Thiery Y., Malet J.-P., Maquaire O. - CNRS, LETG-Geophen, University of Caen-Basse Normandie, Caen, France\nPuissant A. - CNRS, IDEES-GeoSyscom, University of Caen-Basse Normandie, Caen, France\nSterlacchini S. - CNR - Istituto per la Dinamica dei Processi Ambientali (sezione di Milano), Milano, Italia"^^xsd:string ; pubblicazioni:titolo "Landslide susceptibility assessment by bivariate methods at large scales: Application to a complex mountainous environment"^^xsd:string ; prodottidellaricerca:abstract "Statistical assessment of landslide susceptibility has become a major topic of research in the last decade. Most progress has been accomplished on producing susceptibility maps at meso-scales (1:50,000\u00961:25,000). At 1:10,000 scale, which is the scale of production of most regulatory landslide hazard and risk maps in Europe, few tests on the performance of these methods have been performed. This paper presents a procedure to identify the best variables for landslide susceptibility assessment through a bivariate technique (weights of evidence, WOE) and discusses the best way to minimize conditional independence (CI) between the predictive variables. Indeed, violating CI can severely bias the simulated maps by over- or under-estimating landslide probabilities. The proposed strategy includes four steps: (i) identification of the best response variable (RV) to represent landslide events, (ii) identification of the best combination of predictive variables (PVs) and neo-predictive variables (nPVs) to increase the performance of the statistical model, (iii) evaluation of the performance of the simulations by appropriate tests, and (iv) evaluation of the statistical model by expert judgment. The study site is the north-facing hillslope of the Barcelonnette Basin (France), affected by several types of landslides and characterized by a complex morphology. Results indicate that bivariate methods are powerful to assess landslide susceptibility at 1:10,000 scale. However, the method is limited from a geomorphological viewpoint when RVs and PVs are complex or poorly informative. It is demonstrated that expert knowledge has still to be introduced in statistical models to produce reliable landslide susceptibility maps."@en . @prefix ns12: . prodotto:ID20165 pubblicazioni:editore ns12:ID252 ; prodottidellaricerca:prodottoDi modulo:ID2586 , istituto:CDS028 ; pubblicazioni:autoreCNR unitaDiPersonaleInterno:MATRICOLA5850 . @prefix parolechiave: . prodotto:ID20165 parolechiave:insiemeDiParoleChiave . ns11:ID483340 pubblicazioni:rivistaDi prodotto:ID20165 . ns12:ID252 pubblicazioni:editoreDi prodotto:ID20165 . parolechiave:insiemeDiParoleChiaveDi prodotto:ID20165 .