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dc.contributor.authorArabameri, Alireza ( Orcid Icon 0000-0002-1142-1666 )
dc.contributor.authorTiefenbacher, John P. ( Orcid Icon 0000-0001-9342-6550 )
dc.contributor.authorBlaschke, Thomas ( Orcid Icon 0000-0002-1860-8458 )
dc.contributor.authorPradhan, Biswajeet ( Orcid Icon 0000-0001-9863-2054 )
dc.contributor.authorBui, Dieu Tien ( Orcid Icon 0000-0001-5161-6479 )
dc.date.accessioned2021-07-28T17:26:48Z
dc.date.available2021-07-28T17:26:48Z
dc.date.issued2020-03-09
dc.identifier.citationArabameri, A., Tiefenbacher, J. P., Blaschke, T., Pradhan, B., & Bui, D. T. (2020). Morphometric analysis for soil erosion susceptibility mapping using novel GIS-based ensemble model. Remote Sensing, 12(5), 874.en_US
dc.identifier.issn2072-4292
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/14113
dc.description.abstractThe morphometric characteristics of the Kalvārī basin were analyzed to prioritize sub-basins based on their susceptibility to erosion by water using a remote sensing-based data and a GIS. The morphometric parameters (MPs)—linear, relief, and shape—of the drainage network were calculated using data from the Advanced Land-observing Satellite (ALOS) phased-array L-type synthetic-aperture radar (PALSAR) digital elevation model (DEM) with a spatial resolution of 12.5 m. Interferometric synthetic aperture radar (InSAR) was used to generate the DEM. These parameters revealed the network’s texture, morpho-tectonics, geometry, and relief characteristics. A complex proportional assessment of alternatives (COPRAS)-analytical hierarchy process (AHP) novel-ensemble multiple-criteria decision-making (MCDM) model was used to rank sub-basins and to identify the major MPs that significantly influence erosion landforms of the Kalvārī drainage basin. The results show that in evolutionary terms this is a youthful landscape. Rejuvenation has influenced the erosional development of the basin, but lithology and relief, structure, and tectonics have determined the drainage patterns of the catchment. Results of the AHP model indicate that slope and drainage density influence erosion in the study area. The COPRAS-AHP ensemble model results reveal that sub-basin 1 is the most susceptible to soil erosion (SE) and that sub-basin 5 is least susceptible. The ensemble model was compared to the two individual models using the Spearman correlation coefficient test (SCCT) and the Kendall Tau correlation coefficient test (KTCCT). To evaluate the prediction accuracy of the ensemble model, its results were compared to results generated by the modified Pacific Southwest Inter-Agency Committee (MPSIAC) model in each sub-basin. Based on SCCT and KTCCT, the ensemble model was better at ranking sub-basins than the MPSIAC model, which indicated that sub-basins 1 and 4, with mean sediment yields of 943.7 and 456.3 m3km-2year-1, respectively have the highest and lowest SE susceptibility in the study area. The sensitivity analysis revealed that the most sensitive parameters of the MPSIAC model are slope (R2 = 0.96), followed by runoff (R2 = 0.95). The MPSIAC shows that the ensemble model has a high prediction accuracy. The method tested here has been shown to be an effective tool to improve sustainable soil management.en_US
dc.formatText
dc.format.extent24 pages
dc.format.medium1 file (.pdf)
dc.language.isoenen_US
dc.publisherMultidisciplinary Digital Publishing Instituteen_US
dc.sourceRemote Sensing, 2020, Vol. 12, No. 5, Article 874.
dc.subjectSoil erosionen_US
dc.subjectDrainage networken_US
dc.subjectMorphometryen_US
dc.subjectNovel ensemble techniqueen_US
dc.subjectKalvārī Basinen_US
dc.titleMorphometric Analysis for Soil Erosion Susceptibility Mapping Using Novel GIS-Based Ensemble Modelen_US
dc.typepublishedVersion
txstate.documenttypeArticle
dc.rights.holder© 2020 The Authors.
dc.identifier.doihttps://doi.org/10.3390/rs12050874
dc.rights.licenseCreative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
dc.description.departmentGeography


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