Estimation of aboveground biomass and carbon in palustrine wetland using bands and multispectral indices derived from optical satellite imageries PlanetScope and Sentinel-2A

Abstract

Facing the climate change and anthropogenic activities that have been discharging a large proportion of carbon dioxide CO 2 ) into the atmosphere, wetlands stand out as an important sink for CO 2 that is fixed in plant biomass and peatlands. Therefore, quantifying and monitoring wetland biomass is of great importance to preserve carbon stocks. This study aims to explore the potential of multispectral bands and vegetation indices (VIs) derived from PlanetScope and Sentinel-2A sensors to estimate of aboveground biomass (AGB) and organic carbon in AGB (Corg) in the emergent vegetation of a palustrine wetland. We use correlation analysis and linear regression models to examine the relationships between spectral and biophysical variables and verify the best predictor spectral variables for AGB and Corg. Scirpus giganteus vegetation was sampled in the Banhado Grande wetland, in southern Brazil. The VIs were best correlated and preferred as predictor variables. The most accurate model used data from the PlanetScope sensor and VI of photochemical reflectance. Both sensors showed potential for pixel-based estimates of AGB and Corg due to their low RMSE values and their contribution as predictors of biophysical variables, which can contribute to opening new avenues in scientific research focusing on the management, monitoring, and conservation of marshes and your ecosystem service of carbon sink.