Landslide susceptibility assessment in scarce-data regions using remote sensing data

Landslides triggered by rainfall are among the most frequent causes of natural disasters in mountainous terrains. However, landslide susceptibility assessments are often limited due to the scarcity of reliable observations. Due to this lack of data, especially in developing countries, remote sensin...

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Main Authors: Edier Vicente Aristizábal-Giraldo, Diana Ruiz-Vásquez
Format: Article
Language:English
Published: Universidad de Antioquia 2023-10-01
Series:Revista Facultad de Ingeniería Universidad de Antioquia
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Online Access:https://revistas.udea.edu.co/index.php/ingenieria/article/view/351082
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author Edier Vicente Aristizábal-Giraldo
Diana Ruiz-Vásquez
author_facet Edier Vicente Aristizábal-Giraldo
Diana Ruiz-Vásquez
author_sort Edier Vicente Aristizábal-Giraldo
collection DOAJ
description Landslides triggered by rainfall are among the most frequent causes of natural disasters in mountainous terrains. However, landslide susceptibility assessments are often limited due to the scarcity of reliable observations. Due to this lack of data, especially in developing countries, remote sensing is used for landslide susceptibility analysis. This study presents the application of remote sensing data and a logistic regression model to assess landslide susceptibility in a basin on a remote terrain in the northern Colombian Andes, where a rainstorm on May 18th, 2015, triggered more than 40 landslides and an associated debris flow afterwards. The methodology applied is based on free access remote sensing tools, since the study area is considered a scarce-data zone. The results show that free remote sensing tools provide enough information to run a model as logistic regression and achieve a successful first approach to the landslide susceptibility map of complex terrains as the study area. This suggests that the proposed methodology could be implemented in several regions with similar characteristics based only on free access information.
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institution Kabale University
issn 0120-6230
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language English
publishDate 2023-10-01
publisher Universidad de Antioquia
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series Revista Facultad de Ingeniería Universidad de Antioquia
spelling doaj-art-ed7c2a67a1974d0aa381fb35024746be2025-02-09T03:43:56ZengUniversidad de AntioquiaRevista Facultad de Ingeniería Universidad de Antioquia0120-62302422-28442023-10-01112Landslide susceptibility assessment in scarce-data regions using remote sensing dataEdier Vicente Aristizábal-Giraldo0Diana Ruiz-Vásquez1Universidad Nacional de ColombiaUniversidad EAFIT Landslides triggered by rainfall are among the most frequent causes of natural disasters in mountainous terrains. However, landslide susceptibility assessments are often limited due to the scarcity of reliable observations. Due to this lack of data, especially in developing countries, remote sensing is used for landslide susceptibility analysis. This study presents the application of remote sensing data and a logistic regression model to assess landslide susceptibility in a basin on a remote terrain in the northern Colombian Andes, where a rainstorm on May 18th, 2015, triggered more than 40 landslides and an associated debris flow afterwards. The methodology applied is based on free access remote sensing tools, since the study area is considered a scarce-data zone. The results show that free remote sensing tools provide enough information to run a model as logistic regression and achieve a successful first approach to the landslide susceptibility map of complex terrains as the study area. This suggests that the proposed methodology could be implemented in several regions with similar characteristics based only on free access information. https://revistas.udea.edu.co/index.php/ingenieria/article/view/351082Scarce data regionremote sensinglandslide susceptibilitytropical and comple terrains logistic regression
spellingShingle Edier Vicente Aristizábal-Giraldo
Diana Ruiz-Vásquez
Landslide susceptibility assessment in scarce-data regions using remote sensing data
Revista Facultad de Ingeniería Universidad de Antioquia
Scarce data region
remote sensing
landslide susceptibility
tropical and comple terrains
logistic regression
title Landslide susceptibility assessment in scarce-data regions using remote sensing data
title_full Landslide susceptibility assessment in scarce-data regions using remote sensing data
title_fullStr Landslide susceptibility assessment in scarce-data regions using remote sensing data
title_full_unstemmed Landslide susceptibility assessment in scarce-data regions using remote sensing data
title_short Landslide susceptibility assessment in scarce-data regions using remote sensing data
title_sort landslide susceptibility assessment in scarce data regions using remote sensing data
topic Scarce data region
remote sensing
landslide susceptibility
tropical and comple terrains
logistic regression
url https://revistas.udea.edu.co/index.php/ingenieria/article/view/351082
work_keys_str_mv AT ediervicentearistizabalgiraldo landslidesusceptibilityassessmentinscarcedataregionsusingremotesensingdata
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