top of page

ReSEC Lab Published a Study on Evaluation of Semi-Empirical Approaches to Retrieve Satellite-Derived Lake Chlorophyll-a Concentrations

The new study led by ReSEC/Ecohydrology MSc, Ali Reza Shahvaran, published in Remote Sensing Journal. This study We evaluated products of 11 atmospheric correction processors as well as 27 reflectance indexes recommended for Chlorophyll-a (Chl-a) concentration retrieval. These were applied to the western basin of Lake Ontario by pairing 236 satellite scenes from Landsat 5, 7, 8, and Sentinel-2 acquired between 2000 and 2022 to 600 near-synchronous and co-located in situ-measured Chl-a concentrations.

Results suggested that model complexity does not necessarily correlate with improved retrieval accuracy, implying that simpler models should be given appropriate consideration in remote sensing water quality applications. The study adds to the literature on semi-empirical remote sensing Chl-a retrieval approaches that are emerging as essential tools in water quality monitoring that can help protect large freshwater lakes against the undesirable impacts of eutrophication.

The full paper "Comparative Evaluation of Semi-Empirical Approaches to Retrieve Satellite-Derived Chlorophyll-a Concentrations from Nearshore and Offshore Waters of a Large Lake (Lake Ontario)" is available here.


bottom of page