@prefix prodottidellaricerca: . @prefix istituto: . @prefix prodotto: . istituto:CDS028 prodottidellaricerca:prodotto prodotto:ID62120 . @prefix pubblicazioni: . @prefix unitaDiPersonaleInterno: . unitaDiPersonaleInterno:MATRICOLA5850 pubblicazioni:autoreCNRDi prodotto:ID62120 . @prefix unitaDiPersonaleEsterno: . unitaDiPersonaleEsterno:ID4433 pubblicazioni:autoreCNRDi prodotto:ID62120 . @prefix modulo: . modulo:ID2586 prodottidellaricerca:prodotto prodotto:ID62120 . @prefix rdf: . prodotto:ID62120 rdf:type prodotto:TIPO1101 . @prefix retescientifica: . prodotto:ID62120 rdf:type retescientifica:ProdottoDellaRicerca . @prefix rdfs: . prodotto:ID62120 rdfs:label "Landslide Representation Strategies in Susceptibility Studies using Weights-of-Evidence Modeling Technique. (Articolo in rivista)"@en . @prefix xsd: . prodotto:ID62120 pubblicazioni:anno "2007-01-01T00:00:00+01:00"^^xsd:gYear ; pubblicazioni:doi "10.1007/s11053-007-9043-8"^^xsd:string . @prefix skos: . prodotto:ID62120 skos:altLabel "
Poli S.; Sterlacchini S. (2007)
Landslide Representation Strategies in Susceptibility Studies using Weights-of-Evidence Modeling Technique.
in Natural resources research (Dordr., Online)
"^^rdf:HTML ; pubblicazioni:autori "Poli S.; Sterlacchini S."^^xsd:string ; pubblicazioni:paginaInizio "121"^^xsd:string ; pubblicazioni:paginaFine "134"^^xsd:string ; pubblicazioni:numeroVolume "16"^^xsd:string . @prefix ns12: . prodotto:ID62120 pubblicazioni:rivista ns12:ID68759 ; skos:note "Scopus"^^xsd:string ; pubblicazioni:affiliazioni "Department of Environmental Science (DISAT), University of Milan-Bicocca, Piazza della Scienza 1, Milan 20126, Italy.\nInstitute for the Dynamic of Environmental Processes, National Research Council History (CNR-IDPA), Piazza della Scienza 1, Milan 20126, Italy."^^xsd:string ; pubblicazioni:titolo "Landslide Representation Strategies in Susceptibility Studies using Weights-of-Evidence Modeling Technique."^^xsd:string ; prodottidellaricerca:abstract "This paper is focused primarily on how to represent landslide scarp areas, how to analyze results achieved by the application of specific strategies of representation and how to compare the outcomes derived by different tests, within a general framework related to landslide susceptibility assessment. These topics are analyzed taking into account the scale of data survey (1:10,000) and the role of a landslide susceptibility map into projects targeted toward the definition of prediction, prevention, and mitigation measures, in a wider context of civil protection planning. These aims are achieved by using ArcSDM (Arc Spatial Data Modeler), a software extension to ArcView GIS useful for developing spatial prediction models using regional datasets. This extension requires a representation by points of the investigated problems (landslide susceptibility, aquifer vulnerability, detection of mineral deposits, identification of natural habitats of animals, and plants, etc.). Maps of spatial evidence from regional geological and geomorphological datasets were used to generate maps showing susceptibility to slope failures in two different study areas, located in the northern Apennines and in the central Alps (Italy), respectively. The final susceptibility maps for both study areas were derived by the application of the weights-of-evidence (WofE) modeling technique. By this method a series of subjective decisions were required, strongly dependent on an understanding of the natural processes under study, supported by statistical analysis of the spatial associations between known landslides and evidential themes. Except for maps of attitude, permeability, and structure, that were not available for both study areas, the other data were the same and comprised geological, land use, slope, and internal relief maps. The paper illustrates how different representations of scarp areas by points (in terms of different number of points) did not greatly influence the final response map, considering the scale of this work. On the contrary, some differences were observed in the capability of the model to describe the relations between predictor variables and landslides. In effect, a representation of the scarp areas using one point every 50 m led to a more efficient model able to better define relationships of this type. It avoided both problems of redundancy of information, deriving by the use of too many points, and problems related to a random positioning of the centroid. Moreover, it permitted to minimize the uncertainty related with identification and mapping of landslides."@en ; prodottidellaricerca:prodottoDi istituto:CDS028 , modulo:ID2586 ; pubblicazioni:autoreCNR unitaDiPersonaleInterno:MATRICOLA5850 , unitaDiPersonaleEsterno:ID4433 . @prefix parolechiave: . prodotto:ID62120 parolechiave:insiemeDiParoleChiave . ns12:ID68759 pubblicazioni:rivistaDi prodotto:ID62120 . parolechiave:insiemeDiParoleChiaveDi prodotto:ID62120 .