Journal
REMOTE SENSING
Volume 13, Issue 2, Pages -Publisher
MDPI
DOI: 10.3390/rs13020185
Keywords
natural forest; acacia plantation; Random Forest; Synthetic Aperture Radar (SAR); Sentinel-1; Sentinel-2; satellite
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Funding
- Institutional Links grant under the Newton-Vietnam partnership [216372155]
- UK Department of Business, Energy and Industrial Strategy (BEIS)
- Natural Environment Research Council (NERC) [NE/M003574/1]
- United Bank of Carbon (UBoC)
- European Research Council (ERC) under the European Union [771492]
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The study successfully distinguished acacia plantations and natural forests using a combination of radar and optical imagery, identifying an effective parameter for distinguishing between them. Additionally, age classification of acacia plantations was conducted using imagery, with lower accuracy observed for older age classes.
Many remote sensing studies do not distinguish between natural and planted forests. We combine C-Band Synthetic Aperture Radar (Sentinel-1, S-1) and optical satellite imagery (Sentinel-2, S-2) and examine Random Forest (RF) classification of acacia plantations and natural forest in North-Central Vietnam. We demonstrate an ability to distinguish plantation from natural forest, with overall classification accuracies of 87% for S-1, and 92.5% and 92.3% for S-2 and for S-1 and S-2 combined respectively. We found that the ratio of the Short-Wave Infrared Band to the Red Band proved most effective in distinguishing acacia from natural forest. We used RF on S-2 imagery to classify acacia plantations into 6 age classes with an overall accuracy of 70%, with young plantation consistently separated from older. However, accuracy was lower at distinguishing between the older age classes. For both distinguishing plantation and natural forest, and determining plantation age, a combination of radar and optical imagery did nothing to improve classification accuracy.
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