Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy).

Handle URI:
http://hdl.handle.net/10754/617557
Title:
Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy).
Authors:
Lombardo, Luigi; Bachofer, F.; Cama, M.; Märker, M.; Rotigliano, E.
Abstract:
This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north-eastern sector of Sicily (southern Italy), as test site. On 1/10/2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence-only-based statistical method was applied to obtain susceptibility models capable of distinguish future activation sites of debris flow and debris slide, which where the main source failure mechanisms for flow or avalanche type propagation. The set of predictors used in this experiment comprised primary and secondary topographic attributes, derived by processing a high resolution digital elevation model, CORINE land cover data and a set of vegetation and mineral indices obtained by processing multispectral ASTER images. All the selected data sources are dated before the disaster. A spatially random partition technique was adopted for validation, generating fifty replicates for each of the two considered movement typologies in order to assess accuracy, precision and reliability of the models. The debris slide and debris flow susceptibility models produced high performances with the first type being the best fitted. The evaluation of the probability estimates around the mean value for each mapped pixel shows an inverted relation, with the most robust models corresponding to the debris flows. With respect to the role of each predictor within the modelling phase, debris flows appeared to be primarily controlled by topographic attributes whilst the debris slides were better explained by remotely sensed derived indices, particularly by the occurrence of previous wildfires across the slope. The overall excellent performances of the two models suggest promising perspectives for the application of presence-only methods and remote sensing derived predictors. This article is protected by copyright. All rights reserved.
KAUST Department:
Physical Sciences and Engineering (PSE) Division
Citation:
Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy). 2016 Earth Surface Processes and Landforms
Publisher:
Wiley-Blackwell
Journal:
Earth Surface Processes and Landforms
Issue Date:
18-Jul-2016
DOI:
10.1002/esp.3998
Type:
Article
ISSN:
01979337
Additional Links:
http://doi.wiley.com/10.1002/esp.3998
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorLombardo, Luigien
dc.contributor.authorBachofer, F.en
dc.contributor.authorCama, M.en
dc.contributor.authorMärker, M.en
dc.contributor.authorRotigliano, E.en
dc.date.accessioned2016-07-26T09:33:38Z-
dc.date.available2016-07-26T09:33:38Z-
dc.date.issued2016-07-18-
dc.identifier.citationExploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy). 2016 Earth Surface Processes and Landformsen
dc.identifier.issn01979337-
dc.identifier.doi10.1002/esp.3998-
dc.identifier.urihttp://hdl.handle.net/10754/617557-
dc.description.abstractThis study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north-eastern sector of Sicily (southern Italy), as test site. On 1/10/2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence-only-based statistical method was applied to obtain susceptibility models capable of distinguish future activation sites of debris flow and debris slide, which where the main source failure mechanisms for flow or avalanche type propagation. The set of predictors used in this experiment comprised primary and secondary topographic attributes, derived by processing a high resolution digital elevation model, CORINE land cover data and a set of vegetation and mineral indices obtained by processing multispectral ASTER images. All the selected data sources are dated before the disaster. A spatially random partition technique was adopted for validation, generating fifty replicates for each of the two considered movement typologies in order to assess accuracy, precision and reliability of the models. The debris slide and debris flow susceptibility models produced high performances with the first type being the best fitted. The evaluation of the probability estimates around the mean value for each mapped pixel shows an inverted relation, with the most robust models corresponding to the debris flows. With respect to the role of each predictor within the modelling phase, debris flows appeared to be primarily controlled by topographic attributes whilst the debris slides were better explained by remotely sensed derived indices, particularly by the occurrence of previous wildfires across the slope. The overall excellent performances of the two models suggest promising perspectives for the application of presence-only methods and remote sensing derived predictors. This article is protected by copyright. All rights reserved.en
dc.language.isoenen
dc.publisherWiley-Blackwellen
dc.relation.urlhttp://doi.wiley.com/10.1002/esp.3998en
dc.rightsThis is the peer reviewed version of the following article: Lombardo, L., Bachofer, F., Cama, M., Märker, M. and Rotigliano, E., 2016. Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north‐eastern Sicily, Italy). Earth Surface Processes and Landforms., which has been published in final form at http://doi.wiley.com/10.1002/esp.3998. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.en
dc.subjectLandslide susceptibilityen
dc.subjectTriggering mechanism predictionen
dc.subjectASTERen
dc.subjectMaxenten
dc.titleExploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily, Italy).en
dc.typeArticleen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.identifier.journalEarth Surface Processes and Landformsen
dc.eprint.versionPost-printen
dc.contributor.institutionDepartment of Earth and Sea Sciences; University of Palermo; Italyen
dc.contributor.institutionDepartment of Geosciences; University of Tübingenen
dc.contributor.institutionDepartment of Earth and Sea Sciences; University of Palermo; Italyen
dc.contributor.institutionDepartment of Geosciences; University of Tübingenen
dc.contributor.institutionDepartment of Earth and Sea Sciences; University of Palermo; Italyen
dc.contributor.institutionDepartment of Earth Sciences, University of Florence, Italyen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorLombardo, Luigien
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