Mapping Submerged Aquatic Vegetation along the Central Vietnamese Coast Using Multi-Source Remote Sensing

Submerged aquatic vegetation (SAV) in the Khanh Hoa (Vietnam) coastal area plays an important role in coastal communities and the marine ecosystem. However, SAV distribution varies widely, in terms of depth and substrate types, making it difficult to monitor using in-situ measurement. Remote sensing...

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Main Authors: Tran Ngoc Khanh Ni, Hoang Cong Tin, Vo Trong Thach, Cédric Jamet, Izuru Saizen
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:https://www.mdpi.com/2220-9964/9/6/395
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spelling doaj-9d445731448048b99998469f28e72dc82020-11-25T03:59:23ZengMDPI AGISPRS International Journal of Geo-Information2220-99642020-06-01939539510.3390/ijgi9060395Mapping Submerged Aquatic Vegetation along the Central Vietnamese Coast Using Multi-Source Remote SensingTran Ngoc Khanh Ni0Hoang Cong Tin1Vo Trong Thach2Cédric Jamet3Izuru Saizen4Faculty of Environmental Science, University of Sciences, Hue University, Hue City 530000, VietnamFaculty of Environmental Science, University of Sciences, Hue University, Hue City 530000, VietnamNhatrang Institute of Technology Research and Application, Nha Trang City 650000, VietnamLOTUS, University of Science and Technology of Hanoi, Hanoi 100000, VietnamGraduate School of Global Environmental Studies, Kyoto University, Yoshida Honmachi, Sakyo–ku, Kyoto 606–8501, JapanSubmerged aquatic vegetation (SAV) in the Khanh Hoa (Vietnam) coastal area plays an important role in coastal communities and the marine ecosystem. However, SAV distribution varies widely, in terms of depth and substrate types, making it difficult to monitor using in-situ measurement. Remote sensing can help address this issue. High spatial resolution satellites, with more bands and higher radiometric sensitivity, have been launched recently, including the Vietnamese Natural Resources, Environment, and Disaster Monitoring Satellite (VNREDSat-1) (V1) sensor from Vietnam, launched in 2013. The objective of the study described here was to establish SAV distribution maps for South-Central Vietnam, particularly in the Khanh Hoa coastal area, using Sentinel-2 (S2), Landsat-8, and V1 imagery, and then to assess any changes to SAV over the last ten years, using selected historical data. The satellite top-of-atmosphere signals were initially converted to radiance, and then corrected for atmospheric effects. This treated signal was then used to classify Khanh Hoa coastal water substrates, and these classifications were evaluated using 101 in-situ measurements, collected in 2017 and 2018. The results showed that the three satellites could provide high accuracy, with Kappa coefficients above 0.84, with V1 achieving over 0.87. Our results showed that, from 2008 to 2018, SAV acreage in Khanh Hoa was reduced by 74.2%, while gains in new areas compensated for less than half of these losses. This is the first study to show the potential for using V1 and S2 data to assess the distribution status of SAV in Vietnam, and its outcomes will contribute to the conservation of SAV beds, and to the sustainable exploitation of aquatic resources in the Khanh Hoa coastal area.https://www.mdpi.com/2220-9964/9/6/395Submerged aquatic vegetationVNREDSat-1Sentinel-2Landsat-8distribution maptemporal change map
collection DOAJ
language English
format Article
sources DOAJ
author Tran Ngoc Khanh Ni
Hoang Cong Tin
Vo Trong Thach
Cédric Jamet
Izuru Saizen
spellingShingle Tran Ngoc Khanh Ni
Hoang Cong Tin
Vo Trong Thach
Cédric Jamet
Izuru Saizen
Mapping Submerged Aquatic Vegetation along the Central Vietnamese Coast Using Multi-Source Remote Sensing
ISPRS International Journal of Geo-Information
Submerged aquatic vegetation
VNREDSat-1
Sentinel-2
Landsat-8
distribution map
temporal change map
author_facet Tran Ngoc Khanh Ni
Hoang Cong Tin
Vo Trong Thach
Cédric Jamet
Izuru Saizen
author_sort Tran Ngoc Khanh Ni
title Mapping Submerged Aquatic Vegetation along the Central Vietnamese Coast Using Multi-Source Remote Sensing
title_short Mapping Submerged Aquatic Vegetation along the Central Vietnamese Coast Using Multi-Source Remote Sensing
title_full Mapping Submerged Aquatic Vegetation along the Central Vietnamese Coast Using Multi-Source Remote Sensing
title_fullStr Mapping Submerged Aquatic Vegetation along the Central Vietnamese Coast Using Multi-Source Remote Sensing
title_full_unstemmed Mapping Submerged Aquatic Vegetation along the Central Vietnamese Coast Using Multi-Source Remote Sensing
title_sort mapping submerged aquatic vegetation along the central vietnamese coast using multi-source remote sensing
publisher MDPI AG
series ISPRS International Journal of Geo-Information
issn 2220-9964
publishDate 2020-06-01
description Submerged aquatic vegetation (SAV) in the Khanh Hoa (Vietnam) coastal area plays an important role in coastal communities and the marine ecosystem. However, SAV distribution varies widely, in terms of depth and substrate types, making it difficult to monitor using in-situ measurement. Remote sensing can help address this issue. High spatial resolution satellites, with more bands and higher radiometric sensitivity, have been launched recently, including the Vietnamese Natural Resources, Environment, and Disaster Monitoring Satellite (VNREDSat-1) (V1) sensor from Vietnam, launched in 2013. The objective of the study described here was to establish SAV distribution maps for South-Central Vietnam, particularly in the Khanh Hoa coastal area, using Sentinel-2 (S2), Landsat-8, and V1 imagery, and then to assess any changes to SAV over the last ten years, using selected historical data. The satellite top-of-atmosphere signals were initially converted to radiance, and then corrected for atmospheric effects. This treated signal was then used to classify Khanh Hoa coastal water substrates, and these classifications were evaluated using 101 in-situ measurements, collected in 2017 and 2018. The results showed that the three satellites could provide high accuracy, with Kappa coefficients above 0.84, with V1 achieving over 0.87. Our results showed that, from 2008 to 2018, SAV acreage in Khanh Hoa was reduced by 74.2%, while gains in new areas compensated for less than half of these losses. This is the first study to show the potential for using V1 and S2 data to assess the distribution status of SAV in Vietnam, and its outcomes will contribute to the conservation of SAV beds, and to the sustainable exploitation of aquatic resources in the Khanh Hoa coastal area.
topic Submerged aquatic vegetation
VNREDSat-1
Sentinel-2
Landsat-8
distribution map
temporal change map
url https://www.mdpi.com/2220-9964/9/6/395
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