Cargando…

An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping

GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequen...

Descripción completa

Detalles Bibliográficos
Autores principales: Feizizadeh, Bakhtiar, Blaschke, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4786847/
https://www.ncbi.nlm.nih.gov/pubmed/27019609
http://dx.doi.org/10.1080/13658816.2013.869821
_version_ 1782420612322426880
author Feizizadeh, Bakhtiar
Blaschke, Thomas
author_facet Feizizadeh, Bakhtiar
Blaschke, Thomas
author_sort Feizizadeh, Bakhtiar
collection PubMed
description GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC operation yielded poor results.
format Online
Article
Text
id pubmed-4786847
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Taylor & Francis
record_format MEDLINE/PubMed
spelling pubmed-47868472016-03-25 An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping Feizizadeh, Bakhtiar Blaschke, Thomas Int J Geogr Inf Sci Original Articles GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC operation yielded poor results. Taylor & Francis 2014-03-04 2014-01-20 /pmc/articles/PMC4786847/ /pubmed/27019609 http://dx.doi.org/10.1080/13658816.2013.869821 Text en © 2014 The Author(s). Published by Taylor & Francis. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Feizizadeh, Bakhtiar
Blaschke, Thomas
An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping
title An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping
title_full An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping
title_fullStr An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping
title_full_unstemmed An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping
title_short An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping
title_sort uncertainty and sensitivity analysis approach for gis-based multicriteria landslide susceptibility mapping
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4786847/
https://www.ncbi.nlm.nih.gov/pubmed/27019609
http://dx.doi.org/10.1080/13658816.2013.869821
work_keys_str_mv AT feizizadehbakhtiar anuncertaintyandsensitivityanalysisapproachforgisbasedmulticriterialandslidesusceptibilitymapping
AT blaschkethomas anuncertaintyandsensitivityanalysisapproachforgisbasedmulticriterialandslidesusceptibilitymapping
AT feizizadehbakhtiar uncertaintyandsensitivityanalysisapproachforgisbasedmulticriterialandslidesusceptibilitymapping
AT blaschkethomas uncertaintyandsensitivityanalysisapproachforgisbasedmulticriterialandslidesusceptibilitymapping