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  • 1
    Publication Date: 2018-03-08
    Description: This contribution proposes a cautious way of constructing the susceptibility classes obtained from favourability modeling of landslide occurrences. It is based on the ranks of the numerical values obtained by the modelling. Such ranks can be displayed in the form of histograms, cumulative curves, and prediction patterns resembling maps. A number of models have been proposed and in this contribution the following will be compared in terms of their respective rankings for equal area classes: fuzzy set function, empirical likelihood ratio, linear and logistic regression, and Bayesian prediction function. The analyses performed and contrasted exemplify a generalized methodology for comparing predictions that should allow evaluating prediction patterns from any model. Unfortunately, many applications in the scientific literature use methods of characterizing prediction quality that make comparison hard or impossible. A database from a study area in the Mountain Community of Tirano in Valtellina, Lombardy Region, northern Italy, is used to illustrate how the results of the different models and strategies of analysis show the relevance of the properties of the database over those of the models.
    Description: Published
    Description: 1135-1144
    Description: 2TR. Ricostruzione e modellazione della struttura crostale
    Keywords: Landslide susceptibility, spatial support, spatial relationships, prediction models, prediction patterns, target pattern, ranked classes, cross-validation, database signature ; 04.04. Geology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: book chapter
    Location Call Number Expected Availability
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  • 2
    Publication Date: 2018-03-12
    Description: This contribution proposes iterative cross-validation as an approach to assess the quality of spatial predictions of hazardous events. Given the complexity of mathematical procedures and the diversity of geomorphologic applications made to date, STM, the Spatial Target Mapping, is a piece of software, ancillary to a geographical information system and a spreadsheet, that constrains such complexity into a clearly structured framework optimized for modelling. Spatial relationships are established between the distribution of hazardous occurrences and their physical settings to represent in part the slope failure process. They are used in the modelling to anticipate the location of future occurrences. Procedural aspects and computational options are discussed by means of an application to a database developed for landslide susceptibility prediction in northern Italy. Two mathematical models of spatial relationships, fuzzy set function and logistic discriminant function, are applied to generate prediction patterns, prediction-rate tables, and subsequently compute target and uncertainty patterns. The two processing strategies used are sequential elimination and random selection of occurrences for iterative crossvalidations.
    Description: Published
    Description: Santander, Spain
    Description: 2TR. Ricostruzione e modellazione della struttura crostale
    Keywords: Prediction mapping ; Landslide ; Database ; Geographical Information System ; Prediction mapping
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: Conference paper
    Location Call Number Expected Availability
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  • 3
    Publication Date: 2018-03-12
    Description: This contribution proposes a cautious way of constructing the susceptibility classes obtained from favourability modeling of landslide occurrences. It is based on the ranks of the numerical values obtained by the modelling. Such ranks can be displayed in the form of histograms, cumulative curves, and prediction patterns resembling maps. A number of models have been proposed and in this contribution the following will be compared in terms of their respective rankings for equal area classes: fuzzy set function, empirical likelihood ratio, linear and logistic regression, and Bayesian prediction function. The analyses performed and contrasted exemplify a generalized methodology for comparing predictions that should allow evaluating prediction patterns from any model. Unfortunately, many applications in the scientific literature use methods of characterizing prediction quality that make comparison hard or impossible. A database from a study area in the Mountain Community of Tirano in Valtellina, Lombardy Region, northern Italy, is used to illustrate how the results of the different models and strategies of analysis show the relevance of the properties of the database over those of the models.
    Description: Published
    Description: Ljubljana, Slovenia
    Description: 2TR. Ricostruzione e modellazione della struttura crostale
    Keywords: Prediction mapping ; Landslide ; Database ; Geographical Information System ; Advanced in Landslide Science
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: Conference paper
    Location Call Number Expected Availability
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