Poster Session 1, Monday, October 3, 15:40–18:00
Synergy of OLCI sentinel 3A and 3B satellites for filling the gaps in chlorophyll-a products over in southern coastal Vietnam
Under tropical monsoon climate, cloud cover is one of the frequent issues representing the entire Vietnamese coastal water, leading to the failure of different tasks in ocean color remote sensing such as match-up protocols and biogeochemical ocean variables mapping. Here, we combined recently advanced ocean instrument Ocean color Land Instrument (OLCI) data on board Sentinel 3A (S-3A) and 3B (S-3B), with daily revisits for four chlorophyll-a retrieval algorithms (OC4ME, OC4, OC5, OC6) based on water-leaving reflectance obtained from Case 2 Regional CoastColour (C2RCC). To overcome high cloud coverage in the area of interest, full spatial data reconstruction was implemented using Data Interpolating Empirical Orthogonal Functions (DINEOF). By validating against in situ measurements collected in different locations and periods, the OC4ME and OC5 algorithm gave the most accurate prediction for the synergy of OLCI-based chlorophyll-a datasets acquired in both satellites (R2: 0.70, RMSE: 0.844 mg m- 3). DINEOF provides a promising solution to gap-filling spatial information with more than 50% of observations missing. The synergy of satellite S-3A and S-3B, as well as the capacity of gapfilling tools DINEOF, enables the explicit quantifying estimation of biogeochemical variables while effectively addressing cloud cover contamination. The research contributed to the field of remotely sensed ocean color in coastal Vietnam in the context of few studies related to the coastal waters, enabling the potential of quantitative estimation using different bio-optical characteristics following OLCI sensors and future generations.