Changes in mangrove vegetation, aquaculture and paddy cultivation in the Mekong Delta: A study from Ben Tre Province, southern Vietnam

Veettil, Bijeesh Kozhikkodan; Quảng, Ngô Xuân; Trang, Ngô Thị Thu

doi:10.1016/j.ecss.2019.106273

Cited by 52 publications

(20 citation statements)

References 25 publications

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“…For instance, a part of Cau Ngang and Duyen Hai had a considerable area extent of no or almost no vegetation cover due to shrimp farms' development. This finding follows the previously reported research studies in similar coastal areas in the MRD (Hong, Avtar, & Fujii, 2019;Tran et al, 2015;Veettil, Quang, & Thu Trang, 2019). In addition, a dike system around the coastal areas and the fresh water reservoir connected to the South Mang Thit River in the Cang Long district completed in 2011 has promoted more crop cultivation (Toan, 2014;Vinh & Thuc, 2012).…”

Section: The Sustainable Dynamics Of Vegetation Through Land Use and Land Cover Changessupporting

confidence: 88%

“…Monitoring changes in vegetation growth has been the subject of considerable research during the past several decades because of the vital role of vegetation in regulating the terrestrial carbon cycle and the climate system (Piao et al, 2011). Recent studies indicated that the mangrove forest cover in the MRD region had decreased significantly due to shrimp farming expansion (Hong et al, 2019;Tran et al, 2015;Veettil et al, 2019). Besides, our research discovered non-sustainability trends of vegetation changes (including a decrease in natural vegetation and the conversion from natural vegetation to cropland and non-vegetated land).…”

Section: The Research Contribution Towards Achieving the Sustainable Development Goalsmentioning

confidence: 99%

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Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta

Tran

Nguyen

et al. 2021

Land Degrad Dev

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Spatiotemporal analysis and monitoring of vegetation help us investigate ecological health and guide better forest conservation and land management practices for sustainable development. This paper proposes the use of spatial analysis approaches (i.e., ordinary least squares [OLS] and the Hurst exponent) combined with time-series analysis using enhanced vegetation index (EVI) data, derived from LANDSAT via the Google Earth Engine, to estimate the trends and sustainability of vegetation dynamics in the Tra Vinh Province in the Mekong River Delta. We also assessed the EVI changes connected to land change issues to examine the influence of land use conversion on vegetation dynamics. Results show that a large portion of the study area was covered by abundant vegetation (over 50% of the total area), and the increased EVI area was about 5.5-times greater than the area of EVI reduction. Additionally, vegetation sustainability was being seriously compromised (e.g., a decrease in the total area of 8,275 ha) due to several land conversion drivers such as shrimp farming, urbanisation, and industrialisation. Furthermore, results obtained from this research provide insight into the spatiotemporal dynamics of vegetation coverage and reveal the consistency of future vegetation trends. Moreover, the study also quantitatively assessed the positive impacts of Buddhist doctrines on reducing the negative trend of vegetation change in the study area. These findings can lay the ground to formulate sustainable land and environmental plans that meet the 11th, 13th and 15th Sustainable Development Goals (SDGs) (i.e., the sustainable cities and communities, the climate actions, and the life on land). Besides, the analytical procedure adopted in this study can also be applicable to any other coastal areas that require the accurate assessment of vegetation status over time.

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Section: The Sustainable Dynamics Of Vegetation Through Land Use and Land Cover Changessupporting

confidence: 88%

Section: The Research Contribution Towards Achieving the Sustainable Development Goalsmentioning

confidence: 99%

Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta

Tran

Nguyen

et al. 2021

Land Degrad Dev

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“…At present, it has developed a variety of aquaculture modes mainly based on pond culture, supplemented by fish culture in rice fields, animal husbandry, and mangrove aquaculture. The aquaculture in the coastal zone of Vietnam is predicted to increase as a result of climate change, and up to 70% of the Mekong Delta's agricultural land could be subject to saline intrusion this century, which would switch the current rice fields into shrimp farms [44,45]. While aquaculture ponds are playing a critical role in feeding Vietnam's growing population and making billions of dollars through exporting fish and shrimps, the expansion of aquaculture ponds has diminished Vietnam's mangrove forests and caused freshwater and seawater pollution [10,46,47].…”

Section: Study Areamentioning

confidence: 99%

Nation-Scale Mapping of Coastal Aquaculture Ponds with Sentinel-1 SAR Data Using Google Earth Engine

et al. 2020

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Global rapid expansion of the coastal aquaculture industry has made great contributions to enhance food security, but has also caused a series of ecological and environmental issues. Sustainable management of coastal areas requires the explicit and efficient mapping of the spatial distribution of aquaculture ponds. In this study, a Google Earth Engine (GEE) application was developed for mapping coastal aquaculture ponds at a national scale with a novel classification scheme using Sentinel-1 time series data. Relevant indices used in the classification mainly include the water index, texture, and geometric metrics derived from radar backscatter, which were then used to segment and classify aquaculture ponds. Using this approach, we classified aquaculture ponds for the full extent of the coastal area in Vietnam with an overall accuracy of 90.16% (based on independent sample evaluation). The approach, enabling wall-to-wall mapping and area estimation, is essential to the efficient monitoring and management of aquaculture ponds. The classification results showed that aquaculture ponds are widely distributed in Vietnam’s coastal area and are concentrated in the Mekong River Delta and Red River delta (85.14% of the total area), which are facing the increasing collective risk of climate change (e.g., sea level rise and salinity intrusion). Further investigation of the classification results also provides significant insights into the stability and deliverability of the approach. The water index derived from annual median radar backscatter intensity was determined to be efficient at mapping water bodies, likely due to its strong response to water bodies regardless of weather. The geometric metrics considering the spatial variation of radar backscatter patterns were effective at distinguishing aquaculture ponds from other water bodies. The primary use of GEE in this approach makes it replicable and transferable by other users. Our approach lays a solid foundation for intelligent monitoring and management of coastal ecosystems.

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“…Sakamoto et al [19] used Moderate Resolution Imaging Spectroradiometer (MODIS) images to assess the expansion of shrimp ponds and triple rice areas from 2000 to 2006 in the southeastern part of the delta. Several works were conducted for: (1) the southern part [15,20,21], i.e., in Ca Mau province, where inland agriculture and mangrove plants are dominant; (2) the western part, containing grassland [22]; (3) the eastern part [23]; (4) and across the whole region, such as in [2,14,24,25]. In general, the above studies focused on change assessments over short periods.…”

Section: Introductionmentioning

confidence: 99%

Thirty-Year Dynamics of LULC at the Dong Thap Muoi Area, Southern Vietnam, Using Google Earth Engine

Bình¹,

Nhut²,

An³

et al. 2021

IJGI

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The main purpose of this paper is to assess the land use and land cover (LULC) changes for thirty years, from 1990–2020, in the Dong Thap Muoi, a flooded land area of the Mekong River Delta of Vietnam using Google Earth Engine and random forest algorithm. The specific purposes are: (1) determine the main LULC classes and (2) compute and analyze the magnitude and rate of changes for these LULC classes. For the above purposes, 128 Landsat images, topographic maps, land use status maps, cadastral maps, and ancillary data were collected and utilized to derive the LULC maps using the random forest classification algorithm. The overall accuracy of the LULC maps for 1990, 2000, 2010, and 2020 are 88.9, 83.5, 87.1, and 85.6%, respectively. The result showed that the unused land was dominant in 1990 with 28.9 % of the total area, but it was primarily converted to the paddy, a new dominant LULC class in 2020 (45.1%). The forest was reduced significantly from 14.4% in 1990 to only 5.5% of the total area in 2020. Whereas at the same time, the built-up increased from 0.3% to 6.2% of the total area. This research may help the authorities design exploitation policies for the Dong Thap Muoi’s socio-economic development and develop a new, stable, and sustainable ecosystem, promoting the advantages of the region, early forming a diversified agricultural structure.

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Changes in mangrove vegetation, aquaculture and paddy cultivation in the Mekong Delta: A study from Ben Tre Province, southern Vietnam

Cited by 52 publications

References 25 publications

Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta

Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta

Nation-Scale Mapping of Coastal Aquaculture Ponds with Sentinel-1 SAR Data Using Google Earth Engine

Thirty-Year Dynamics of LULC at the Dong Thap Muoi Area, Southern Vietnam, Using Google Earth Engine

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