Remote Sensing Approach for Monitoring Coastal Wetland in the Mekong Delta, Vietnam: Change Trends and Their Driving Forces

Dang, An T. N.; Kumar, Lalit; Reid, Michael; Nguyen, Ho

doi:10.3390/rs13173359

Cited by 39 publications

(15 citation statements)

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“…Similar accuracy results have been reported in Dang and Mucsi study which also used a pixel-based method for land cover classification in the Binh Duong province [39]. The relatively high accuracies in land cover classification using medium satellite images such as Landsat and MLC method have also been demonstrated in previous studies [40][41][42][43].…”

Section: ) Classification and Accuracy Assessmentsupporting

confidence: 85%

Assessing Vegetation Cover Change Using Remote Sensing: Case Study at Binh Duong Province, Vietnam

et al. 2022

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This study aims to present the application of remote sensing in monitoring vegetation change in Binh Duong Province, Vietnam. The study used Landsat 5 images in the year 2010 and Landsat 8 images in the years 2015 and 2020 to investigate the area of vegetation. The maximum likelihood classification method (MLC) was used to classify land cover and an accuracy matrix was computed to validate the classification results. The references data were collected to support classification and accuracy assessment processes including land use maps in 2010, 2015, and 2020. In addition, collected field points and UAV (unmanned aerial vehicle) in 2020 were used. The overall accuracies are 81.27%, 84.41%, and 83.86%, and Kappa indices were 0.76, 0.80, and 0.80, corresponding to 2010, 2015, and 2020. The results showed that as compared to 2010 and 2015, the area of vegetation in 2020 decreased 10% and 8%, respectively. The average vegetation cover per capita was 740 m2 person-1 in 2020, compared to 1000 m2 person-1 in 2015 and 1200 m2 person-1 in 2010. This reduction was obvious in urban areas in the province, due to the need for construction and development. The study provides meaningful information on vegetation change and green area per capita in Binh Duong Province from 2010 to 2020.

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Section: ) Classification and Accuracy Assessmentsupporting

confidence: 85%

Assessing Vegetation Cover Change Using Remote Sensing: Case Study at Binh Duong Province, Vietnam

et al. 2022

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“…Transitional marshes in the Mekong Delta include brackish grasslands, which are affected by brackish water and are inundated on a daily basis due to tides (Buckton et al 1999). There were no transitional marshes in wetland classification for the year 2020 since these marshes occur with small areas in the study area and so consisted of mixed pixels and were not classified using Landsat imagery by Dang et al (2021c). However, this wetland category increased under future SLR scenarios according to the SLAMM output due to the fact that SLR lower elevation of more lands in the study area for inundation.…”

Section: Projections Of Melaleuca/forested Wetlands Under Future Slr ...mentioning

confidence: 99%

“…The wetland map in the present study was acquired from Landsat 8 OLI images in 2020 from Dang et al (2021c) and used as initial map for the prediction of climatic suitability under future SLR scenarios. The wetland map at 15-m spatial resolution was clipped with the DEM to have the identical extent and cell size.…”

Section: Wetland Mapmentioning

confidence: 99%

“…Despite these important ecosystems services, Melaleuca wetlands in the Mekong Delta, Vietnam, are under considerable risk due to climate change and sea-level rise (SLR) in addition to threats caused by local anthropogenic activities. These activities, such as the development of rice production, aquaculture practices and clearance of the Melaleuca forests for fuels and wood products, are significant causes of the Melaleuca wetland loss (Dang et al 2021c). Importantly, climate change brings extreme seasonal variation in temperature and prolonged drought, which threaten Melaleuca wetlands due to forest fire issues (Thanh et al 2020;Dang et al 2021b; Van et al 2021).…”

Section: Introductionmentioning

confidence: 99%

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Coastal Melaleuca wetlands under future climate and sea-level rise scenarios in the Mekong Delta, Vietnam: vulnerability and conservation

Dang

Reid

Kumar³

2023

Reg Environ Change

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Melaleuca wetland ecosystems play crucial roles in ecology and human livelihood, yet the ecosystems are vulnerable to climate change and relative sea-level rise (SLR) impacts. Documents and research on climate change and SLR impacts on coastal Melaleuca wetlands in the Mekong Delta, Vietnam, are currently limited. Therefore, the present study aimed to identify changes in habitat suitability for a coastal Melaleuca wetland species in response to different future climate change and SLR scenarios, in the West Sea of the Mekong Delta, with the aid of an ensemble species distribution model (SDM) and the Sea Level Affecting Marshes Model (SLAMM). Melaleuca species occurrence records, bioclimatic and eco-physiological variables were utilized to predict potential distribution of the species in response to current and future climate scenarios (i.e. RCP4.5 and 8.5) for the year 2070. Wetland maps for 2020, a digital elevation model (DEM) and localized site-specific parameters (i.e. historic trend of SLR, erosion, subsidence and overwash) were utilized as input data for SLAMM to simulate spatial distribution of Melaleuca/forested wetlands under the two SLR scenarios. The final habitat suitability for the Melaleuca wetland species was identified based on these two resultant datasets, climatic suitability and spatial distribution of the wetlands. Simulated results suggested mean losses in suitable habitat of 29.8% and 58.7% for stable and subsidence scenarios, respectively, for the year 2070 in comparison to the baseline scenario. SLR combined with considerable subsidence rate was suggested as one of the main drivers responsible for the habitat suitability loss. The findings obtained from the current work are useful sources for planning conservation areas for the Melaleuca wetlands, to protect and preserve the ecosystems and their important services under future climate and SLR scenarios.

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“…Sea-level rise associated with global climate change has resulted in freshwater sources being salty and no longer suitable for domestic and production activities. In Vietnam, the sea level rose by about 14 cm between 1995 and 2019, and it was expected to be higher than 15 cm in 2020 using the Hon Dau 1992 datum [10]. Thus, seawater intrusion has deteriorated freshwater sources such as groundwater in Bac Lieu province [11] and in Soc Trang province [12], and surface water in Ca Mau peninsula [13].…”

Section: Introductionmentioning

confidence: 99%

Major concerns of surface water quality in south-west coastal regions of Vietnamese Mekong Delta

Giao

Phan

Huynh

2022

Preprint

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This study aimed to appraise seasonal variations in surface water quality on the coasts of Southwestern Vietnam using entropy-weighted water quality index (EWQI) and multivariate statistics: cluster analysis (CA), principal component analysis (PCA), and discriminant analysis (DA). Forty-nine samples monitored in Kien Giang province during the rainy and dry seasons were analysed for 16 physiochemical and biological parameters. Compared to the Vietnamese standard, surface water quality in the study areas was contaminated with organic matter (high BOD and COD), nutrients (high NH4+-N, NO2ˉ-N, and PO43ˉ-P), TSS, Fe, and coliform. Seasonal variations in surface water quality in the coastal regions were observed. TSS, organic matter and microbial problems in water bodies tend to be more serious in the rainy seasons due to an increase in water flow containing pollutants from the upstream and wastes from regional human activities. Meanwhile, the salinity in the dry season (0-31.8 ‰) was greatly higher, which caused only 10% of samples to be suitable for irrigation. CA extracted 11 and 13 clusters from 49 locations in the dry and rainy seasons, respectively. 5PCs obtained from PCA can explain 74.79% and 70.34% of total water quality variations in dry and rainy seasons, respectively. Moreover, the results of PCA suggested that natural factors (hydrological regimes, temperature, rainfall, sea-level rise) and human sources (domestic, agriculture, industry, and tourism) are accountable for these fluctuations. DA extracted 7 parameters (pH, TSS, salinity, Fe, NO3ˉ-N, NH4+-N, and Clˉ) for leading the difference in water quality, with 87.76% of correct assignation. EWQI revealed that 65.5% of total samples were classified as a very bad quality for drinking in the dry season. However, this ratio declined to 59.2% in the rainy season. Although the surface water quality was slightly improved during the rainy season, organic matter and microbial pollution need to be concerned. The findings of this study can provide insights into seasonal variations in surface water with the application of multivariate statistics and EWQI, which could support policymakers in developing water management strategies.

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Remote Sensing Approach for Monitoring Coastal Wetland in the Mekong Delta, Vietnam: Change Trends and Their Driving Forces

Cited by 39 publications

References 100 publications

Assessing Vegetation Cover Change Using Remote Sensing: Case Study at Binh Duong Province, Vietnam

Assessing Vegetation Cover Change Using Remote Sensing: Case Study at Binh Duong Province, Vietnam

Coastal Melaleuca wetlands under future climate and sea-level rise scenarios in the Mekong Delta, Vietnam: vulnerability and conservation

Major concerns of surface water quality in south-west coastal regions of Vietnamese Mekong Delta

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