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A Novel Rule-Based Approach in Mapping Landslide Susceptibility

Despite recent advances in developing landslide susceptibility mapping (LSM) techniques, resultant maps are often not transparent, and susceptibility rules are barely made explicit. This weakens the proper understanding of conditioning criteria involved in shaping landslide events at the local scale...

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Autores principales: Roodposhti, Majid Shadman, Aryal, Jagannath, Pradhan, Biswajeet
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567231/
https://www.ncbi.nlm.nih.gov/pubmed/31100945
http://dx.doi.org/10.3390/s19102274
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author Roodposhti, Majid Shadman
Aryal, Jagannath
Pradhan, Biswajeet
author_facet Roodposhti, Majid Shadman
Aryal, Jagannath
Pradhan, Biswajeet
author_sort Roodposhti, Majid Shadman
collection PubMed
description Despite recent advances in developing landslide susceptibility mapping (LSM) techniques, resultant maps are often not transparent, and susceptibility rules are barely made explicit. This weakens the proper understanding of conditioning criteria involved in shaping landslide events at the local scale. Further, a high level of subjectivity in re-classifying susceptibility scores into various classes often downgrades the quality of those maps. Here, we apply a novel rule-based system as an alternative approach for LSM. Therein, the initially assembled rules relate landslide-conditioning factors within individual rule-sets. This is implemented without the complication of applying logical or relational operators. To achieve this, first, Shannon entropy was employed to assess the priority order of landslide-conditioning factors and the uncertainty of each rule within the corresponding rule-sets. Next, the rule-level uncertainties were mapped and used to asses the reliability of the susceptibility map at the local scale (i.e., at pixel-level). A set of If-Then rules were applied to convert susceptibility values to susceptibility classes, where less level of subjectivity is guaranteed. In a case study of Northwest Tasmania in Australia, the performance of the proposed method was assessed by receiver operating characteristics’ area under the curve (AUC). Our method demonstrated promising performance with AUC of 0.934. This was a result of a transparent rule-based approach, where priorities and state/value of landslide-conditioning factors for each pixel were identified. In addition, the uncertainty of susceptibility rules can be readily accessed, interpreted, and replicated. The achieved results demonstrate that the proposed rule-based method is beneficial to derive insights into LSM processes.
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spelling pubmed-65672312019-06-17 A Novel Rule-Based Approach in Mapping Landslide Susceptibility Roodposhti, Majid Shadman Aryal, Jagannath Pradhan, Biswajeet Sensors (Basel) Article Despite recent advances in developing landslide susceptibility mapping (LSM) techniques, resultant maps are often not transparent, and susceptibility rules are barely made explicit. This weakens the proper understanding of conditioning criteria involved in shaping landslide events at the local scale. Further, a high level of subjectivity in re-classifying susceptibility scores into various classes often downgrades the quality of those maps. Here, we apply a novel rule-based system as an alternative approach for LSM. Therein, the initially assembled rules relate landslide-conditioning factors within individual rule-sets. This is implemented without the complication of applying logical or relational operators. To achieve this, first, Shannon entropy was employed to assess the priority order of landslide-conditioning factors and the uncertainty of each rule within the corresponding rule-sets. Next, the rule-level uncertainties were mapped and used to asses the reliability of the susceptibility map at the local scale (i.e., at pixel-level). A set of If-Then rules were applied to convert susceptibility values to susceptibility classes, where less level of subjectivity is guaranteed. In a case study of Northwest Tasmania in Australia, the performance of the proposed method was assessed by receiver operating characteristics’ area under the curve (AUC). Our method demonstrated promising performance with AUC of 0.934. This was a result of a transparent rule-based approach, where priorities and state/value of landslide-conditioning factors for each pixel were identified. In addition, the uncertainty of susceptibility rules can be readily accessed, interpreted, and replicated. The achieved results demonstrate that the proposed rule-based method is beneficial to derive insights into LSM processes. MDPI 2019-05-16 /pmc/articles/PMC6567231/ /pubmed/31100945 http://dx.doi.org/10.3390/s19102274 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Roodposhti, Majid Shadman
Aryal, Jagannath
Pradhan, Biswajeet
A Novel Rule-Based Approach in Mapping Landslide Susceptibility
title A Novel Rule-Based Approach in Mapping Landslide Susceptibility
title_full A Novel Rule-Based Approach in Mapping Landslide Susceptibility
title_fullStr A Novel Rule-Based Approach in Mapping Landslide Susceptibility
title_full_unstemmed A Novel Rule-Based Approach in Mapping Landslide Susceptibility
title_short A Novel Rule-Based Approach in Mapping Landslide Susceptibility
title_sort novel rule-based approach in mapping landslide susceptibility
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567231/
https://www.ncbi.nlm.nih.gov/pubmed/31100945
http://dx.doi.org/10.3390/s19102274
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