Estimation of chlorophyll concentration on surface water bodies from hyperspectral satellite data


  • Martina Frezza
  • Valeria La Pegna
  • Davide De Santis
  • Dario Cappelli
  • Fabio Del Frate


PRISMA, Sentinel-3, Water Quality, Trophic level, Neural Networks


This research contributes to advancing the measurement and monitoring of crucial biogeophysical parameters, serving as both qualitative and quantitative indicators for the assessment of natural surface conditions. Leveraging hyperspectral satellite sensors, the primary objective is to enhance the management of natural resources. A key focus of this investigation is the concentration of chlorophyll, a pivotal indicator for assessing phytoplankton abundance and algal biomass in aquatic environments. Chlorophyll concentration emerges as a valuable metric for gauging water quality, understanding the biophysical state of water bodies, discerning trophic levels, and evaluating the eutrophication status of water. The imperative to estimate chlorophyll concentration through satellite-derived data stems from inherent limitations in in-situ measurements. Traditional field measurements conducted by pertinent Regional Environmental Protection Agency entities are labor-intensive, allowing for only a sparse sampling frequency, typically limited to a few measurements annually. Furthermore, these in-situ measurements offer data at specific points, potentially overlooking the spatial variability of chlorophyll concentration across water bodies. By leveraging hyperspectral satellite technology, this research aims to overcome these limitations, providing a more comprehensive and spatially distributed understanding of chlorophyll concentration. This holistic approach not only enhances the efficiency of resource management but also contributes to a more nuanced comprehension of the dynamic ecological processes within aquatic ecosystems.