Spracklen, B and Spracklen, DV orcid.org/0000-0002-7551-4597 (2021) Synergistic Use of Sentinel-1 and Sentinel-2 to Map Natural Forest and Acacia Plantation and Stand Ages in North-Central Vietnam. Remote Sensing, 13 (2). 185. ISSN 2072-4292
Abstract
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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Copyright, Publisher and Additional Information: | © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). | ||||||
Keywords: | natural forest; acacia plantation; Random Forest; Synthetic Aperture Radar (SAR); Sentinel-1; Sentinel-2; satellite | ||||||
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Institution: | The University of Leeds | ||||||
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) | ||||||
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Depositing User: | Symplectic Publications | ||||||
Date Deposited: | 22 Jan 2021 16:57 | ||||||
Last Modified: | 22 Jan 2021 16:57 | ||||||
Status: | Published | ||||||
Publisher: | MDPI | ||||||
Identification Number: | https://doi.org/10.3390/rs13020185 |