Please use this identifier to cite or link to this item:
http://hdl.handle.net/2122/11137| DC Field | Value | Language |
|---|---|---|
| dc.date.accessioned | 2018-03-12T13:11:07Z | en |
| dc.date.available | 2018-03-12T13:11:07Z | en |
| dc.date.issued | 2017-06 | en |
| dc.identifier.uri | http://hdl.handle.net/2122/11137 | en |
| dc.description.abstract | 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. | en |
| dc.language.iso | English | en |
| dc.relation.ispartof | CIMNE International Centre for Numerical Methods in Engineering | en |
| dc.rights | CC0 1.0 Universal | en |
| dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | en |
| dc.subject | Prediction mapping | en |
| dc.subject | Landslide | en |
| dc.subject | Database | en |
| dc.subject | Geographical Information System | en |
| dc.title | Spatial target mapping: an approach to susceptibility prediction based on iterative crossvalidations | en |
| dc.type | Conference paper | en |
| dc.description.status | Published | en |
| dc.subject.INGV | Prediction mapping | en |
| dc.description.ConferenceLocation | Santander, Spain | en |
| dc.relation.references | Chung, C.F. and Fabbri, A.G., 1993. Representation of geoscience data for information integration. Journal of Non-renewable Resources, 2 (2): 122-139. Chung, C.F. and Fabbri, A.G., 1999. Probabilistic prediction models for landslide hazard mapping. Photogrammetric Engineering & Remote Sensing, PE&RS, 65 (12): 1389-1399. Chung, C.F. and Fabbri, A.G., 2001. Prediction models for landslide hazard using fuzzy set approach. In, M. Marchetti and V. Rivas, eds., Geomorphology and Environmental Impact Assessment, Balkema, Rotterdam, p. 31-47. Fabbri A.G., Cavallin A., Masetti M., Poli S., Sterlacchini S., and Chung C.J., 2010. Spatial uncertainty of groundwater-vulnerability predictions assessed by a cross-validation strategy: an application to nitrate concentrations in the Province of Milan, Northern Italy. In, C.A. Brebbia, ed., Risk Analysis VII and Brownfields V, Southampton, Wit Press, p.PI-497-514, or WIT Transactions on Information and Communication Technologies, vol. 43, www.witpress.com, ISSN 1743-3517 (on-line) doi:10.2495/RISKJ100421.Fabbri, A.G., Cavallin, A., Patera, A., Sangalli, L. and Chung, C.-J., 2017. Comparing patterns of spatial relationships for susceptibility prediction of landslide occurrences. In M. Mikos et al. (eds), Advancing Culture of Living with Landslides. Proceedings of the 4th World Landslide Forum, Ljubljana, Springer International Publishing AG 2017, DOI 10.1007/978-3-319-53498- 5_129, in press. Fabbri A.G., Chung C.-J., 2009. Training decision-makers in hazard spatial prediction and risk assessment: ideas, tools, strategies and challenges. In, K. Duncan and C. A. Brebbia, eds., Disaster Management and Human Health Risk. Southampton, WIT Press, p. 285-296. Fabbri A.G. and Chung C.-J., 2012. A spatial prediction modeling system for mineral potential and natural hazard mapping. Proceedings of EUREGEO2012, v. II, p. 756-757, Bologna, Italy, June 12-15, 2012. Fabbri, A.G., Chung, C.F. & Jang, D. H., 2004. A software approach to spatial predictions of natural hazards and consequent risks. Risk Analysis IV, C.A. Brebbia, (ed.), Boston, WIT Press: Southampton, pp. 289-305. SpatialModels, STM software: http://www.spatialmodels.com | en |
| dc.description.obiettivoSpecifico | 2TR. Ricostruzione e modellazione della struttura crostale | en |
| dc.contributor.author | Fabbri, Andrea G. | en |
| dc.contributor.author | Patera, Antonio | en |
| dc.contributor.author | Chung, Chang-Jo | en |
| dc.contributor.department | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Roma1, Roma, Italia | en |
| dc.contributor.editor | Alonso, Elisa | en |
| dc.contributor.editor | Corominas, Jordi | en |
| dc.contributor.editor | Hurlimann, M | en |
| item.openairetype | Conference paper | - |
| item.cerifentitytype | Publications | - |
| item.languageiso639-1 | en | - |
| item.grantfulltext | restricted | - |
| item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
| item.fulltext | With Fulltext | - |
| crisitem.author.dept | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Roma1, Roma, Italia | - |
| crisitem.author.orcid | 0000-0001-7641-4689 | - |
| crisitem.author.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
| crisitem.department.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
| Appears in Collections: | Conference materials | |
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| Fabbri_Patera_Chung_TALUDES_def_edited.pdf | Paper | 863.06 kB | Adobe PDF |
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