A benchmark dataset and workflow for landslide susceptibility zonation-Reference-Cited by-同舟云学术

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A benchmark dataset and workflow for landslide susceptibility zonation

Published:2024-09 Issue: Volume: Page:104927
ISSN:0012-8252
Container-title:Earth-Science Reviews
language:en
Short-container-title:Earth-Science Reviews

Author:

Alvioli Massimiliano,Loche Marco,Jacobs Liesbet,Grohmann Carlos H.,Abraham Minu Treesa,Gupta Kunal,Satyam Neelima,Scaringi Gianvito,Bornaetxea Txomin,Rossi Mauro,Marchesini Ivan,Lombardo Luigi,Moreno Mateo,Steger Stefan,Camera Corrado,Bajni Greta,Samodra Guruh,Wahyudi Erwin Eko,Susyanto Nanang,Sinčić Marko,Gazibara Sanja Bernat,Sirbu Flavius,Torizin Jewgenij,Schüßler Nick,Mirus Benjamin,Woodard Jacob,Aguilera Héctor,Rivera-Rivera Jhonatan Steven

Publisher

Elsevier BV

Reference161 articles.

1. Statistical pattern integration for mineral exploration;Agterberg,1990

2. On the prediction of landslide occurrences and sizes via Hierarchical Neural Networks;Aguilera;Stoch. Env. Res. Risk A.,2022

3. Ensemble learning on the benchmark dataset for landslide susceptibility zonation in Central Italy;Aguilera,2023

4. A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at İzmir, Turkey;Akgun;Landslides,2012

5. Landslide susceptibility mapping for a landslide–prone area (Findikli, NE of Turkey) by likelihood–frequency ratio and weighted linear combination models;Akgun;Environ. Geol.,2008

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