A novel method for river bank detection from Landsat satellite data : a case study in the Vietnamese Mekong Delta

River 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 studie...

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Main Authors: Binh, Doan Van, Wietlisbach, Basil, Kantoush, Sameh, Loc, Ho Huu, Park, Edward, de Cesare, Giovanni, Cuong, Do Huy, Tung, Nguyen Xuan, Sumi, Tetsuya
Other Authors: Asian School of the Environment
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/145961
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1459612023-02-28T16:41:15Z A novel method for river bank detection from Landsat satellite data : a case study in the Vietnamese Mekong Delta Binh, Doan Van Wietlisbach, Basil Kantoush, Sameh Loc, Ho Huu Park, Edward de Cesare, Giovanni Cuong, Do Huy Tung, Nguyen Xuan Sumi, Tetsuya Asian School of the Environment Engineering::Environmental engineering Remote Sensing Landsat River 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. Published version 2021-01-18T07:37:04Z 2021-01-18T07:37:04Z 2020 Journal Article Binh, 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/rs12203298 2072-4292 https://hdl.handle.net/10356/145961 10.3390/rs12203298 2-s2.0-85092934206 20 12 en Remote Sensing © 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/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Environmental engineering
Remote Sensing
Landsat
spellingShingle Engineering::Environmental engineering
Remote Sensing
Landsat
Binh, Doan Van
Wietlisbach, Basil
Kantoush, Sameh
Loc, Ho Huu
Park, Edward
de Cesare, Giovanni
Cuong, Do Huy
Tung, Nguyen Xuan
Sumi, Tetsuya
A novel method for river bank detection from Landsat satellite data : a case study in the Vietnamese Mekong Delta
description River 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.
author2 Asian School of the Environment
author_facet Asian School of the Environment
Binh, Doan Van
Wietlisbach, Basil
Kantoush, Sameh
Loc, Ho Huu
Park, Edward
de Cesare, Giovanni
Cuong, Do Huy
Tung, Nguyen Xuan
Sumi, Tetsuya
format Article
author Binh, Doan Van
Wietlisbach, Basil
Kantoush, Sameh
Loc, Ho Huu
Park, Edward
de Cesare, Giovanni
Cuong, Do Huy
Tung, Nguyen Xuan
Sumi, Tetsuya
author_sort Binh, Doan Van
title A novel method for river bank detection from Landsat satellite data : a case study in the Vietnamese Mekong Delta
title_short A novel method for river bank detection from Landsat satellite data : a case study in the Vietnamese Mekong Delta
title_full A novel method for river bank detection from Landsat satellite data : a case study in the Vietnamese Mekong Delta
title_fullStr A novel method for river bank detection from Landsat satellite data : a case study in the Vietnamese Mekong Delta
title_full_unstemmed A novel method for river bank detection from Landsat satellite data : a case study in the Vietnamese Mekong Delta
title_sort novel method for river bank detection from landsat satellite data : a case study in the vietnamese mekong delta
publishDate 2021
url https://hdl.handle.net/10356/145961
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