## Data and Methods
### Remote Sensing Datasets  
The Sentinel-2A images were obtained from the Sentinel Scientific Data Hub (ESA) in the 13 bands of the multispectral instrument (MSI) sensor. The visible (blue, green, and red) and near-infrared (NIR) bands have a spatial resolution of 10 m, and the red edge (RE5, RE6, RE7, and RE8A) and shortwave infrared (SWIR1 and SWIR2) bands have a spatial resolution of 20 m. Band 1 (coastal aerosol), band 9 (water vapor), and band 10 (cirrus) were excluded and not considered in this research. The product was already orthorectified, georeferenced, and radiometrically calibrated into top-of-atmosphere (ToA) reflectance data, with pre-processing level 1C. The images were pre-processed to level 2A to remove atmospheric effects and convert pixel values to surface reflectance using the Sen2 Cor standalone tool [46], but can be processed alternatively in the S2A toolbox of the Sentinel Application Platform (SNAP). Bands with resolution of 10 m were downscaled to 20 m to ensure that all channels were concatenated with aligned pixels using the nearest-neighbor method in the SNAP geometric operation toolbox. Figure 2: Biological form of vegetation: (**A**) emergent; (**B**) amphibious. Collection of the vegetation: (**C**) image after the vegetation cut. Source: authors, 2018. Sentinel-2A and PlanetScope data were obtained as closely as possible to the vegetation collection dates (Table 1). Among the PlanetScope satellite constellations, we used data from Planetscope-0, sometimes called Dove data, which detects the blue, green, red, and NIR spectral bands. The Ortho Scene PlanetScope product was made available to the research team through the Planet Research and Education Program on the Planet Explorer website, with atmospherically corrected level 3B surface reflectance and 3 m spatial resolution. The Ortho Scene product is distributed in images with radiance values (Planet Analytic product) and reflectance values (planet surface reflectance--SR). The SR product is derived from the Planet Analytic product, and the bands are co-acquired, orthorectified and georeferenced, with radiometric calibration in surface reflectance derived using the 6S radiative transfer code, assuming a continental aerosol model and using the closest available MODIS aerosol optical depth spatially and temporally, which guarantees consistency in all climatic conditions, minimizing the uncertainty of the spectral response in time and location [47]. In addition to the single-band information, we derived vegetation indices (VIs) based on the band mathematics of the sensors' reflectance images. The VIs were computed as indicated in Table 2.  
These VIs were chosen because they are conceptually linked to the aforementioned vegetative processes and considered effective in characterizing and predicting AGB and Corg [12; 51]. Among the VIs, the NDVI is often used successfully to estimate vegetation biomass in wetlands [7; 54] and in studies related to photosynthesis, carbon stocks, and other plant-related processes [55]. Moreover, we used specific VIs adapted for wetlands, which are versions of the NDVI and EVI, such as the normalized difference aquatic vegetation index (NDAVI) and the water-adjusted vegetation index (WAVI). In terms of estimating Corg, the indices of photochemical reflectance (sPRI) and integrated index (CO\({}_{2}\)Flux) are sensitive to changes in carotenoid pigments in leaves, indicative of the efficiency of the use of photosynthetic light related to the level of carbon dioxide stored by vegetation and vegetation vigor [56]. CO\({}_{2}\)Fluxis an integrated index formed by the sPRI and NDVI VIs. A modified CO\({}_{2}\)Flux index replacing the traditional NDVI with an NDVI adapted for wetlands (NDAVI) was also used. The spectral values of the bands and VIs were obtained from the pixels corresponding to the points of each sample site on Banhado Grande from automatic extraction.