The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLVIII-3-2024
https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-89-2024
https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-89-2024
07 Nov 2024
 | 07 Nov 2024

Assessment of Phytoplankton Biomass and Diversity in Northeast Brazil via Satellite Ocean Color Observation

Erick Vinicius Correia da Cunha, Pedro Augusto Mendes de Castro Melo, Gabriel Bittencourt Farias, and Vincent Vantrepotte

Keywords: Ocean Color, Phytoplankton, Remote Sensing, Chlorophyll a

Abstract. The study investigates the distribution and seasonal dynamics of phytoplankton communities in Northeast Brazil using ocean color data obtained through satellite remote sensing (RS). This unprecedented approach for the region assesses the biomass and composition of phytoplankton, which is crucial for understanding the responses of the marine ecosystem to environmental changes and impacts on biogeochemical cycles. The research uses in situ data from oceanographic campaigns (MARSEAL, ABRACOS and SWOT) and satellite data from sources such as OC-CCI (multi-mission), GlobColour (multi-mission) and Sentinel-3 OLCI (single sensor). These datasets allow for the analysis of chlorophyll-a (chl a), phytoplankton functional types (PFTs) and phytoplankton size classes (PSCs), with a focus on in situ sampling periods. For chl a, the correlation observed between the in situ data from the campaigns and the OC-CCI satellite data was explained by some statistical descriptors with the coefficient of determination (R2) explaining approximately 34% of the variation in the in situ samples, with a root mean square deviation (RMSD) of around 0.2926 and mean absolute percentage deviation (MAPD) and mean bias error (MBE) values of −18.7361% and −2.3454%, respectively. As for the in situ data for the accessory pigment 19'Hexfucoxanthin (19HF) from the ABRACOS campaigns, which was correlated with the satellite data from the model by El Hourany et al. (2019), the R2, RMSD, MAPD and MBE were 58%, 0.1815, −4.528% and 0.5411%, respectively.