10.3389/fmars.2019.00598.s001 Shukla Poddar Shukla Poddar Neethu Chacko Neethu Chacko Debadatta Swain Debadatta Swain Table_1_Estimation of Chlorophyll-a in Northern Coastal Bay of Bengal Using Landsat-8 OLI and Sentinel-2 MSI Sensors.docx Frontiers 2019 chlorophyll-a ocean color Landsat-8 Sentinel-2 COMAPS Bay of Bengal 2019-10-01 08:34:54 Dataset https://frontiersin.figshare.com/articles/dataset/Table_1_Estimation_of_Chlorophyll-a_in_Northern_Coastal_Bay_of_Bengal_Using_Landsat-8_OLI_and_Sentinel-2_MSI_Sensors_docx/9923693 <p>Chlorophyll-a can be used as a proxy for phytoplankton and thus is an essential water quality parameter. The presence of phytoplankton in the ocean causes selective absorption of light by chlorophyll-a pigment resulting in change of the ocean color that can be identified by ocean color remote sensing. The accuracy of chlorophyll-a concentration (Chl-a) estimated from remote sensing sensors depends on the bio-optical algorithm used for the retrieval in specific regional waters. In this work, it is attempted to estimate Chl-a from two currently active satellite sensors with relatively good spatial resolutions considering ocean applications. Suitability of two standard bio-optical Ocean Color (OC) Chlorophyll algorithms, OC-2 (2-band) and OC-3 (3-band) in estimating Chl-a for turbid waters of the northern coastal Bay of Bengal is assessed. Validation with in-situ data showed that OC-2 algorithm gives an estimate of Chl-a with a better correlation of 0.795 and least bias of 0.35 mg/m<sup>3</sup>. Further, inter-comparison of Chl-a retrieved from the two sensors, Landsat-8 OLI and Sentinel-2 MSI was also carried out. The variability of Chl-a during winter, pre-monsoon, and post-monsoon seasons over the study region were inter-compared. It is observed that during pre-monsoon and post-monsoon seasons, Chl-a from MSI is over estimated compared to OLI. This work is a preliminary step toward estimation of Chl-a in the coastal oceans utilizing available better spatially resolved sensors.</p>