Articles | Volume 22, issue 4
https://doi.org/10.5194/nhess-22-1395-2022
https://doi.org/10.5194/nhess-22-1395-2022
Research article
 | 
21 Apr 2022
Research article |  | 21 Apr 2022

Assessing the importance of conditioning factor selection in landslide susceptibility for the province of Belluno (region of Veneto, northeastern Italy)

Sansar Raj Meena, Silvia Puliero, Kushanav Bhuyan, Mario Floris, and Filippo Catani

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Cited articles

ARPAV: Cambiamenti climatici, per l'IPCC i tempi stringono, Il focus sul Veneto, https://www.arpa.veneto.it/temi-ambientali/meteo/riferimenti/documenti/documenti-meteo/IPCC E CAMBIAMENTI CLIMATICI IN VENETO.pdf (last access: 9 April 2022), 2021. 
Baglioni, A., Tosoni, D., De Marco, P., and Arziliero, L.: Analisi del dissesto da frana in Veneto, ISPRA, https://www.isprambiente.gov.it/contentfiles/00003200/3228-capitolo-10-veneto.pdf (last access: 9 April 2022), 2006. 
Baird, C.: Comparison of Risk Assessment Instruments in Juvenile Justice, NCCD, https://www.njjn.org/uploads/digital-library/NCCD_risk-assessment-comparison_August-2013.pdf (last access: 9 April 2022), 2013. 
Boretto, G., Crema, S., Marchi, L., Monegato, G., Arziliero, L., and Cavalli, M.: Assessing the effect of the Vaia storm on sediment source areas and connectivity storm in the Liera catchment (Dolomites), in: EGU General Assembly 2021, online, 19–30 April 2021, EGU21-7643, https://doi.org/10.5194/egusphere-egu21-7643, 2021. 
Brabb, E. E., Pampeyan, E. H., and Bonilla, M. G.: Landslide susceptibility in San Mateo County, California, Reston, VA, Report 360, https://doi.org/10.3133/mf360, 1972. 
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Short summary
The study investigated the importance of the conditioning factors in predicting landslide occurrences using the mentioned models. In this paper, we evaluated the importance of the conditioning factors (features) in the overall prediction capabilities of the statistical and machine learning algorithms.
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