Abstract
This study proposes a hybrid intelligence approach based on an extreme
gradient boosting regression and genetic algorithm, namely, the XGBR-GA
model, incorporating Sentinel-2, Sentinel-1, and ALOS-2 PALSAR-2 data to
estimate the mangrove above-ground biomass (AGB), including small and
shrub mangrove patches in the Red River Delta biosphere reserve across
the northern coast of Vietnam. We used the novel extreme gradient
boosting decision tree (XGBR) technique together with genetic algorithm
(GA) optimization for feature selection to construct and verify a
mangrove AGB model using data from a field survey of 105 sampling plots
conducted in November and December of 2018 and incorporated the dual
polarimetric (HH and HV) data of the ALOS-2 PALSAR-2 L-band and the
Sentinel-2 multispectral data combined with Sentinel-1 (C-band VV and
VH) data. We employed the root-mean-square error (RMSE) and coefficient
of determination (R2) to
evaluate the performance of the proposed model. The capability of the
XGBR-GA model was assessed via a comparison with other machine-learning
(ML) techniques, i.e., the CatBoost regression (CBR), gradient boosted
regression tree (GBRT), support vector regression (SVR), and random
forest regression (RFR) models. The XGBR-GA model yielded a promising
result (R2 = 0.683, RMSE = 25.08 Mg·ha−1) and outperformed the four other ML models. The XGBR-GA model retrieved a mangrove AGB ranging from 17 Mg·ha−1 to 142 Mg·ha−1 (with an average of 72.47 Mg·ha−1).
Therefore, multisource optical and synthetic aperture radar (SAR)
combined with the XGBR-GA model can be used to estimate the mangrove AGB
in North Vietnam. The effectiveness of the proposed method needs to be
further tested and compared to other mangrove ecosystems in the tropics.
Original language | English |
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Article number | 1334 |
Pages (from-to) | 1-24 |
Number of pages | 24 |
Journal | Remote Sensing |
Volume | 12 |
Issue number | 8 |
DOIs | |
Publication status | Published - 2 Apr 2020 |
Externally published | Yes |
Bibliographical note
Copyright the Author(s) 2020. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- Sentinel-2
- Sentinel-1
- ALOS-2 PALSAR-2
- mangrove
- above-ground biomass
- extreme gradient boosting regression
- genetic algorithm
- North Vietnam