Identification of erosion-prone areas using different multi-criteria decision-making techniques and gis

Arabameri, A; Pradhan, B; Pourghasemi, HR; Rezaei, K

Identification of erosion-prone areas using different multi-criteria decision-making techniques and gis

Arabameri, A Pradhan, B

Pourghasemi, HR Rezaei, K

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Publication Type:: Journal Article
Citation:: Geomatics, Natural Hazards and Risk, 2018, 9 (1), pp. 1129 - 1155
Issue Date:: 2018-10-30

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Field	Value	Language
dc.contributor.author	Arabameri, A	en_US
dc.contributor.author	Pradhan, B https://orcid.org/0000-0001-9863-2054	en_US
dc.contributor.author	Pourghasemi, HR	en_US
dc.contributor.author	Rezaei, K	en_US
dc.date.issued	2018-10-30	en_US
dc.identifier.citation	Geomatics, Natural Hazards and Risk, 2018, 9 (1), pp. 1129 - 1155	en_US
dc.identifier.issn	1947-5705	en_US
dc.identifier.uri	http://hdl.handle.net/10453/130842
dc.description.abstract	© 2018 The Author(s). The awareness of erosion risk in watersheds provides the possibility of identifying critical areas and prioritising protective and management plans. Soil erosion is one of the major natural hazards in the rainy mountainous regions of the Neka Roud Watershed in Mazandaran Province, Iran. This research assesses soil erosion susceptibility through morphometric parameters and the land use/land cover (LU/LC) factor based on multiple-criteria decision-making (MCDM) techniques, remote sensing and GIS. A set of 17 linear, relief and shape morphometric parameters and 5 LU/LC classes are used in the analysis. The aforementioned factors are selected as indicators of soil erosion in the study area. Then, four MCDM models, namely, the new additive ratio assessment (ARAS), complex proportional assessment (COPRAS), multi-objective optimisation by ratio analysis and compromise programming, are applied to the prioritisation of the Neka Roud sub-watersheds. The Spearman’s correlation coefficient test and Kendall’s tau correlation coefficient test indices are used to select the best models. The validation of the models indicates that the ARAS and COPRAS models based on morphometric parameters and LU/LC classes, respectively, achieve the best performance. The results of this research can be used by planners and decision makers in soil conservation and in reducing soil erosion.	en_US
dc.relation.ispartof	Geomatics, Natural Hazards and Risk	en_US
dc.relation.isbasedon	10.1080/19475705.2018.1513084	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Identification of erosion-prone areas using different multi-criteria decision-making techniques and gis	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	9	en_US
utslib.for	0406 Physical Geography and Environmental Geoscience	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	open_access	*
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	9	en_US

Abstract:

© 2018 The Author(s). The awareness of erosion risk in watersheds provides the possibility of identifying critical areas and prioritising protective and management plans. Soil erosion is one of the major natural hazards in the rainy mountainous regions of the Neka Roud Watershed in Mazandaran Province, Iran. This research assesses soil erosion susceptibility through morphometric parameters and the land use/land cover (LU/LC) factor based on multiple-criteria decision-making (MCDM) techniques, remote sensing and GIS. A set of 17 linear, relief and shape morphometric parameters and 5 LU/LC classes are used in the analysis. The aforementioned factors are selected as indicators of soil erosion in the study area. Then, four MCDM models, namely, the new additive ratio assessment (ARAS), complex proportional assessment (COPRAS), multi-objective optimisation by ratio analysis and compromise programming, are applied to the prioritisation of the Neka Roud sub-watersheds. The Spearman’s correlation coefficient test and Kendall’s tau correlation coefficient test indices are used to select the best models. The validation of the models indicates that the ARAS and COPRAS models based on morphometric parameters and LU/LC classes, respectively, achieve the best performance. The results of this research can be used by planners and decision makers in soil conservation and in reducing soil erosion.

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http://hdl.handle.net/10453/130842