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Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas

This work aims at evaluating the sensitivity of landslide susceptibility mapping (LSM) to sampling design in lithologically-heterogeneous areas. We hypothesize that random sampling of the landslide absence data in such areas can be biased by statistical aggregation of the explanatory variables, whic...

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Autores principales: Dornik, Andrei, Drăguţ, Lucian, Oguchi, Takashi, Hayakawa, Yuichi, Micu, Mihai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826312/
https://www.ncbi.nlm.nih.gov/pubmed/35136155
http://dx.doi.org/10.1038/s41598-022-06257-w
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author Dornik, Andrei
Drăguţ, Lucian
Oguchi, Takashi
Hayakawa, Yuichi
Micu, Mihai
author_facet Dornik, Andrei
Drăguţ, Lucian
Oguchi, Takashi
Hayakawa, Yuichi
Micu, Mihai
author_sort Dornik, Andrei
collection PubMed
description This work aims at evaluating the sensitivity of landslide susceptibility mapping (LSM) to sampling design in lithologically-heterogeneous areas. We hypothesize that random sampling of the landslide absence data in such areas can be biased by statistical aggregation of the explanatory variables, which impact the model outputs. To test this hypothesis, we train a Random Forest (RF) model in two different domains, as follows: (1) in lithologically heterogeneous areas, and (2) in lithologically homogeneous domains of the respective areas. Two heterogeneous areas are selected in Japan (125 km(2)) and Romania (497 km(2)), based on existing landslide inventories that include 371 and 577 scarps, respectively. These areas are divided into two, respectively three domains, defined by lithological units that reflect relatively homogeneous topographies. Fourteen terrain attributes are derived from a 30 m SRTM digital elevation model and employed as explanatory variables. Results show that LSM is sensitive to a random sampling of the absence data in lithologically heterogeneous areas. Accuracy measures improve significantly when sampling and LSM are conducted in lithologically homogeneous domains, as compared to heterogeneous areas, reaching an increase of 9% in AUC and 17% in the Kappa index.
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spelling pubmed-88263122022-02-10 Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas Dornik, Andrei Drăguţ, Lucian Oguchi, Takashi Hayakawa, Yuichi Micu, Mihai Sci Rep Article This work aims at evaluating the sensitivity of landslide susceptibility mapping (LSM) to sampling design in lithologically-heterogeneous areas. We hypothesize that random sampling of the landslide absence data in such areas can be biased by statistical aggregation of the explanatory variables, which impact the model outputs. To test this hypothesis, we train a Random Forest (RF) model in two different domains, as follows: (1) in lithologically heterogeneous areas, and (2) in lithologically homogeneous domains of the respective areas. Two heterogeneous areas are selected in Japan (125 km(2)) and Romania (497 km(2)), based on existing landslide inventories that include 371 and 577 scarps, respectively. These areas are divided into two, respectively three domains, defined by lithological units that reflect relatively homogeneous topographies. Fourteen terrain attributes are derived from a 30 m SRTM digital elevation model and employed as explanatory variables. Results show that LSM is sensitive to a random sampling of the absence data in lithologically heterogeneous areas. Accuracy measures improve significantly when sampling and LSM are conducted in lithologically homogeneous domains, as compared to heterogeneous areas, reaching an increase of 9% in AUC and 17% in the Kappa index. Nature Publishing Group UK 2022-02-08 /pmc/articles/PMC8826312/ /pubmed/35136155 http://dx.doi.org/10.1038/s41598-022-06257-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Dornik, Andrei
Drăguţ, Lucian
Oguchi, Takashi
Hayakawa, Yuichi
Micu, Mihai
Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas
title Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas
title_full Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas
title_fullStr Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas
title_full_unstemmed Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas
title_short Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas
title_sort influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826312/
https://www.ncbi.nlm.nih.gov/pubmed/35136155
http://dx.doi.org/10.1038/s41598-022-06257-w
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