Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta. (29th March 2021)
- Record Type:
- Journal Article
- Title:
- Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta. (29th March 2021)
- Main Title:
- Characterising spatiotemporal vegetation variations using LANDSAT time‐series and Hurst exponent index in the Mekong River Delta
- Authors:
- Tran, Thuong V.
Tran, Duy X.
Nguyen, Ho
Latorre‐Carmona, Pedro
Myint, Soe W. - Abstract:
- Abstract: 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 groundAbstract: 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. … (more)
- Is Part Of:
- Land degradation & development. Volume 32:Number 13(2021)
- Journal:
- Land degradation & development
- Issue:
- Volume 32:Number 13(2021)
- Issue Display:
- Volume 32, Issue 13 (2021)
- Year:
- 2021
- Volume:
- 32
- Issue:
- 13
- Issue Sort Value:
- 2021-0032-0013-0000
- Page Start:
- 3507
- Page End:
- 3523
- Publication Date:
- 2021-03-29
- Subjects:
- coastal area -- EVI -- linear regression model -- spatial analysis -- Tra Vinh
Land degradation -- Periodicals
Soil conservation -- Periodicals
Reclamation of land -- Periodicals
Land use -- Periodicals
Economic development -- Environmental aspects -- Periodicals
333.7315 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/ldr.3934 ↗
- Languages:
- English
- ISSNs:
- 1085-3278
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5146.796790
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 19455.xml