Quantifying Mangrove aboveground biomass changes: Analysis of conservation impact in blue forests projects using sentinel-2 satellite imagery

Abstract

Achieving a precise assessment of the aboveground biomass (AGB) in mangroves is a critical foundation for sustainable management and carbon sequestration assessment within climate change mitigation strategies. Conserving existing mangrove forests can maintain and enhance AGB over time. This study used a support vector regression (SVR) model, and vegetation indices derived from Sentinel-2 data for a comparative analysis of mangrove AGB within conservation and restoration projects in Madagascar and Abu Dhabi Emirate. The results confirmed that the SVR model based on vegetation indices, once calibrated against the field inventory data, was effective for estimating mangrove AGB at project scale. For the Madagascar project, the model achieved an R2 of 0.81 and RMSE of 27.99 Mg ha−1 for the 2015 timepoint, and an R2 of 0.79 and RMSE of 32.82 Mg ha−1 for 2019. In Abu Dhabi, an R2 of 0.76 and RMSE of 20.51 Mg ha−1 in 2015 and R2 of 0.75 and RMSE of 22.29 Mg ha−1 in 2020 were obtained. The SVR model estimated a decline in AGB from 116.78 Mg ha−1 to 109.63 Mg ha−1 during 2015–2019 in Madagascar, representing a decrease of 7.15 Mg ha−1 (6.13%). While in Abu Dhabi, the average AGB was estimated at 37.51 Mg ha−1 in 2015 and 42.69 Mg ha−1 in 2020, indicating an increase of 5.18 Mg ha−1 (13.76%) which can be attributed to conservation efforts in this region. This study suggested that Sentinel-2 can facilitate the comparison of AGB changes before and after conservation efforts, enabling the quantification of long-term shifts in mangrove AGB.