Validation of the atmospheric correction of Landsat OLI imagery and turbidity retrievals using AERONET-OC data from the Bahía Blanca site

ARENA, MAXIMILIANO; DELGADO, ANA LAURA; PRATOLONGO, PAULA D.; CELLERI, CARLA; VITALE, ALEJANDRO JOSÉ

San Juan

Workshop; 2021 XIX Workshop on Information Processing and Control (RPIC); 2022

AERONET-OC collects data from worldwidedistributed autonomous CE-318 sun-photometers adapted toprovide measurements of the radiance emerging from the sea(i.e., water-leaving radiance). The network supports satelliteocean color validation activities through standardizedmeasurements performed at different sites with a singlemeasuring system and protocol. In January 2020 the BahíaBlanca site was established at the mouth of the main navigationchannel of the Bahía Blanca Estuary, a complex system wherewidespread erosion and strong tidal currents are responsible forthe typically high suspended loads in the channel. In this work wepresent a validation of three different algorithms for theatmospheric correction of Landsat-OLI scenes over the area,based on AERONET-OC data and in situ measurementsobtained with a hand-held spectroradiometer. Surface remotesensing reflectance was used to retrieve satellite turbidity and thealgorithm performance was tested using turbidity measurementsobtained from water samples collected simultaneously withsatellite overpasses. According to our results, the best fit wasobtained with the atmospheric correction algorithm based on theblack-pixel assumption, with the aerosol type estimated using thetwo OLI-SWIR bands and allowed to vary spatially (per pixelvariable epsilon). The aerosol type changed along the estuary,with an epsilon parameter that commonly decreased from theinner section through the mouth. The regression line of in situmeasurements with satellite turbidity showed a goodperformance (R2 = 0.97, n=20), with a high accuracy (RMSE =4.03, NMAE= 0.16) and no tendency to over or underestimation(BIAS = 0.63). The application of properly validated algorithmsto satellite data from high spatial resolution images allowed forthe identification of detailed turbidity features in the estuary,resulting from re‐suspension phenomena over banks andturbulent currents.