Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/145961
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dc.contributor.authorBinh, Doan Vanen_US
dc.contributor.authorWietlisbach, Basilen_US
dc.contributor.authorKantoush, Samehen_US
dc.contributor.authorLoc, Ho Huuen_US
dc.contributor.authorPark, Edwarden_US
dc.contributor.authorde Cesare, Giovannien_US
dc.contributor.authorCuong, Do Huyen_US
dc.contributor.authorTung, Nguyen Xuanen_US
dc.contributor.authorSumi, Tetsuyaen_US
dc.date.accessioned2021-01-18T07:37:04Z-
dc.date.available2021-01-18T07:37:04Z-
dc.date.issued2020-
dc.identifier.citationBinh, D. V., Wietlisbach, B., Kantoush, S., Loc, H. H., Park, E., de Cesare, G., . . . Sumi, T. (2020). A novel method for river bank detection from Landsat satellite data : a case study in the Vietnamese Mekong Delta. Remote Sensing, 12(20), 3298-. doi:10.3390/rs12203298en_US
dc.identifier.issn2072-4292en_US
dc.identifier.urihttps://hdl.handle.net/10356/145961-
dc.description.abstractRiver bank (RB) erosion is a global issue affecting livelihoods and properties of millions of people. However, it has not received enough attention in the Vietnamese Mekong Delta (VMD), i.e., the world’s third largest delta, compared to salinity intrusion and flooding. There have been several studies examining RB and coastal erosion in the VMD using remotely sensed satellite data, but the applied methodology was not adequately validated. Therefore, we developed a novel SRBED (Spectral RB Erosion Detection) method, in which the M-AMERL (Modified Automated Method for Extracting Rivers and Lakes) is proposed, and a new RB change detection algorithm using Landsat data. The results show that NDWI (Normalized Difference Water Index) and MNDWI (Modified Normalized Difference Water Index) using the M-AMERL algorithm (i.e., NDWIM-AMERL, MNDWIM-AMERL) perform better than other indices. Furthermore, the NDWIM-AMERL; SMA (i.e., NDWIM-AMERL using the SMA (Spectral Mixture Analysis) algorithm) is the best RB extraction method in the VMD. The NDWIM-AMERL; SMA performs better than the MNDWI, NDVI (Normalized Difference Vegetation Index), and WNDWI (Weighted Normalized Difference Water Index) indices by 35–41%, 70% and 30%, respectively. Moreover, the NDVI index is not recommended for assessing RB changes in the delta. Applying the developed SRBED method and RB change detection algorithm, we estimated a net erosion area of the RB of –1.5 km2 from 2008 to 2014 in the Tien River from Tan Chau to My Thuan, with a mean erosion width of –2.64 m and maximum erosion widths exceeding 60 m in places. Our advanced method can be applied in other river deltas having similar characteristics, and the results from our study are helpful in future studies in the VMD.en_US
dc.language.isoenen_US
dc.relation.ispartofRemote Sensingen_US
dc.rights© 2020 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/).en_US
dc.subjectEngineering::Environmental engineeringen_US
dc.titleA novel method for river bank detection from Landsat satellite data : a case study in the Vietnamese Mekong Deltaen_US
dc.typeJournal Articleen
dc.contributor.schoolAsian School of the Environmenten_US
dc.identifier.doi10.3390/rs12203298-
dc.description.versionPublished versionen_US
dc.identifier.scopus2-s2.0-85092934206-
dc.identifier.issue20en_US
dc.identifier.volume12en_US
dc.subject.keywordsRemote Sensingen_US
dc.subject.keywordsLandsaten_US
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item.grantfulltextopen-
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