Remote sensing data is another possible option for mapping chlorophyll-a (Chl-a), which is present in all phytoplankton species. This study estimates chlorophyll-a concentration in Lagos Lagoon using Landsat 7 (ETM+) and Landsat 8 (OLI) data. Landsat data were first geometrically corrected. The techniques used were band rationing and regression modeling. The brightness values were converted to reflectance through the radiometric correction process, while the regression model, logarithmically transformed chlorophyll-a, was used as the dependent variable. The single bands, band ratios, and logarithmically transformed band ratios were used as the independent variables. Subsequently, the R2 values were computed and calculated using the results generated from regression models. The Chl-a concentration generated showed reasonable results, but the concentrations across the study lagoon were impacted by the ocean current with distance from Atlantic Ocean.

The study concluded that the Landsat 7 and 8 images were effective in estimating chl-a concentration and producing chl-a spatio-temporal map