Chlorophyll-a level data update from seawifs images using Landsat-7 data

Abstract

The current lack of continuous and temporal monitoring of Chlorophyll-a in certain regions is evident. There are some platforms that collected this data in the past, without current update. For this reason, a model based on a Random Forest classification was trained using the limnological classification based on chlorophyll-a concentration from SeaWiFS data and extrapolated to Landsat-7. The model achieved an accuracy of 62.29% with a moderate kappa coefficient. This approach allowed the development of a well-performing model capable of efficiently monitoring and updating chlorophyll-a data in a region lacking in-situ sensors for this variable.