http://www.cnr.it/ontology/cnr/individuo/prodotto/ID107537
Assessment of the spatial agreement of landslide susceptibility maps (Abstract/Poster in atti di convegno)
- Type
- Label
- Assessment of the spatial agreement of landslide susceptibility maps (Abstract/Poster in atti di convegno) (literal)
- Anno
- 2009-01-01T00:00:00+01:00 (literal)
- Alternative label
Ballabio C., Blahut J. & Sterlacchini S. (2009)
Assessment of the spatial agreement of landslide susceptibility maps
in EGU - European Geosciences Union, Vienna, Austria, 19-24 April 2009
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Ballabio C., Blahut J. & Sterlacchini S. (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- Proceedings of EGU - European Geosciences Union (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
- Geophysical Research Abstracts, Vol. 11, EGU2009-9480-1 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Ballabio C. - Dipartimento di Scienze dell'Ambiente e del Territorio, Università degli Studi di Milano-Bicocca, Italia
Blahut J. - Dipartimento di Scienze dell'Ambiente e del Territorio, Università degli Studi di Milano-Bicocca, Italia
Sterlacchini S. - CNR - Istituto per la Dinamica dei Processi Ambientali (sezione di Milano), Milano, Italia (literal)
- Titolo
- Assessment of the spatial agreement of landslide susceptibility maps (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autoriVolume
- AA.VV. - International Scientific Committee of EGU (literal)
- Abstract
- Indirect assessment of landslide susceptibility provides planners and decision-makers with a practical and
cost-effective way to zone areas susceptible to landsliding. This goal can be achieved by applying statistic models
to estimate the spatial probability of slope instability within the investigated area.
It is also of crucial importance to assess the accuracy of the model outcome. To this purpose, cross-validation
techniques, based on independent samples, are usually adopted. However further attention has to be paid to the
evaluation of the spatial variability of the predicted results. In this work, the assessment of the statistical relations
between the landslides and the controlling geo-environmental factors was used to produce a series of landslide
susceptibility maps. A quantitative data-driven model (Weights of Evidence modeling technique) was applied at a
regional scale for a study area site in Central Italian Alps (Valtellina di Tirano).
The landslides present within this area were identified from aerial photographs, field surveys and exiting
inventories; consequently, two different landslide inventory maps at scale 1:10000, were produced for the
study, each one characterized by a different level of accuracy. The goodness of fit and prediction capabilities of
susceptibility maps was evaluated through the use of success-rate and prediction-rate curves.
Using different landslide inventories, a series of different combinations of predisposing factors were utilized
to produce different susceptibility maps, each one classified in 5 and 10 classes. Subsequently, Kappa
Statistic, and Principal Component analysis were performed to measure the classification agreement among the
maps produced by models using different combinations of support covariates.
This analysis have shown that despite the substantially identical prediction rate of different models, the spatial
agreement of these maps is non consistent, as their spatial pattern is considerably different. This result in problems
connected with the use of success and prediction rates curves as an exhaustive measure of accuracy for spatial data. (literal)
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