Estimation of chlorophyll-a concentration using ground data and Sentinel-2 and Landsat-8 Satellite images processing (Case study: Tiab Estuary)

The estuaries are one of the most important coastal natural resources. Chlorophyll-a (Chl-a) monitoring, which is the pigment of oceanic and coastal phytoplankton, can be measured and evaluated using new remote sensing technology. The presence of blue, green and red wavelengths in oceanic observation satellites has always paved the way for monitoring the color of the oceans. The aim of this study is used OC2 and OC3 bio-optical algorithms and Sentinel-2 MSI and Landsat-8 OLI satellite data in April 2019 to estimate chlorophyll-a concentration in the estuary Tiap area. Ground sampling data were carried out to correlate and evaluate the results. The results showed that the OC2 algorithm in Landsat-8 and Sentinel-2 satellites had the highest R Squared coefficient (R2) 0.91 and 0.64, respectively, and the Root mean square error (RMSe) of the satellite images were 0.13 and 0.33, respectively. These results indicate the high accuracy of the OC2 algorithm in the satellite images used and were selected as the most suitable algorithm for mapping chlorophyll-a concentration in the study area.