**5. Conclusions**

We report the first attempt to incorporate Sentinel-2 and ALOS-2 PALSAR-2 data into the extreme gradient boosting regression (XGBR) model and thereby estimate the mangrove AGB in Vietnam's Can Gio biosphere reserve. The XGBR model outperformed four other machine learning models in mangrove AGB retrieval in the study area. When provided with the Sentinel-2 and ALOS-2 PALSAR-2 data, XGBR estimated the mangrove AGB with satisfactory accuracy (*R*<sup>2</sup> = 0.805, RMSE = 28.13 Mg ha−1). Interestingly, we found that new vegetation indices derived from the Sentinel-2 data, such as the Normalized Difference Index (NDI45) and the Inverted Red-Edge Chlorophyll Index (IRECl), sensitively detected mangrove AGB in the biosphere reserve. In future investigations, the proposed approach should be tested in other tropical forest ecosystems.

**Author Contributions:** Conceptualization, T.D.P., L.V.N., N.N.L.; methodology, T.D.P.; validation, T.D.P., N.N.L., N.T.H.; data analysis, N.N.L., T.D.P., N.T.H.; field investigation, L.V.N., L.Q.K., T.T.T., H.X.T.; writing—original draft preparation, T.D.P., N.N.L., N.T.H.; writing—review and editing, T.D.P., N.N.L., J.X., N.T.H., N.Y.; visualization, T.D.P., L.V.N.; supervision, N.Y., W.T., All authors have read and approved the final version of this paper. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** The authors would like to thank the Japan Aerospace Exploration Agency (JAXA) for providing the ALOS-2 PALSAR-2 data for this research under the 2nd Earth Observation Research Announcement Collaborative Research Agreement between the JAXA and RIKEN AIP. The authors are grateful to mission No. VAST 01.07/20-21 from the Vietnam Academy of Science and Technology (VAST) for data support of this research.

**Conflicts of Interest:** The authors declare no conflict of interest.
