Characterizing Spatiotemporal Patterns of Mangrove Forests in Can Gio Biosphere Reserve Using Sentinel-2 Imagery

Characterizing Spatiotemporal Patterns of Mangrove Forests in Can Gio Biosphere Reserve Using Sentinel-2 Imagery

This study aimed at evaluating the spatiotemporal patterns of mangrove forest variations for three ecological zones of the Can Gio biosphere reserve (i.e., core, buffer, and transition zones) and its relation to land use/land cover changes. Time series Sentinel-2 Imagery—which presents the Normalize...

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Bibliographic Details
Published in:Applied sciences Vol. 10; no. 12; p. 4058
Main Authors: Le, Hoa T., Tran, Thuong V., Gyeltshen, Sangay, Nguyen, Chau P. T., Tran, Duy X., Luu, Tung H., Duong, Man B.
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-06-2020
Subjects:
Aquaculture
Biosphere
Biosphere reserves
Buffer zones
Classification
Climate change
coastal area
Distribution
Economic development
Ecosystems
Forecasts and trends
Forest management
Forests
Imagery
Land cover
Land use
Local government
LULC
Mangrove swamps
Methods
NDVI
overlap similarity algorithm
Population studies
Protection and preservation
satellite imagery
Satellite imaging
Satellites
Shielding
Studies
Time series
Topography
Tourism
Vegetation
Vegetation cover
Vegetation mapping
Vietnam
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Summary:This study aimed at evaluating the spatiotemporal patterns of mangrove forest variations for three ecological zones of the Can Gio biosphere reserve (i.e., core, buffer, and transition zones) and its relation to land use/land cover changes. Time series Sentinel-2 Imagery—which presents the Normalized Different Vegetation Index (NDVI), obtained through the Google Earth Engine and Overlap Similarity Algorithm—was used to characterize vegetation cover in the study area. Furthermore, the Cohen’s Kappa agreement was applied to examine the accuracy of mangrove classification, and the Mann–Kendal (MK) significance was used to analyze the spatiotemporal trends of mangrove forests. The results showed that an NDVI value greater than 0.3 recorded the reflected signal of mangrove population in the study area with an O-index greater than 0.85. A Cohen’s Kappa statistic of agreement of 0.7 and an overall classification accuracy of 83% was obtained. Regarding the trend in mangrove forest patterns, an increase in area of 669 ha and 579 ha explored at the buffer and core zones, respectively, while the largest declined mangrove area of 350 ha was investigated at the buffer zone, followed by a transition at 314 ha during the study period due to the interconversion of shrimp farming and the expansion of built-up areas. Moreover, the study also described the negative impacts of the sea-encroached urban-tourism zone on mangrove patterns in the foreseeable future. The results from this study will act as a basic fundamental authentic report for local governments in proposing strategies for the shielding of mangrove forests and economic development from negative consequences in foreseeable future.
ISSN:2076-3417
2076-3417
DOI:10.3390/app10124058