Abstract
ABSTRACT Chlorophyll-a (Chl-a) concentrations serve as a pivotal metric for assessing the biological content and eutrophication levels of waterbodies. In optical remote sensing, empirical and semi-analytical methods are commonly employed for Chl-a retrieval. Leveraging the Level-1B remote sensing data from the Directional Polarimetric Camera (DPC) aboard the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS), this study amalgamates empirical algorithms (OC2, OC3, Aiken-P, and Aiken-C) and look-up-table (LUT) techniques to estimate Chl-a in open water. Test data acquired from DPC on 20 August 2022, are validated against the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra satellite and AERONET-Ocean Color water-leaving radiance data for the same area and date. The results reveal that among the tested algorithms, particularly in the log10 scale space, the Aiken-P algorithm demonstrates the highest correlation coefficient (R2 = 0.6333), with the lowest bias of 1.0366 and a minimum mean absolute error (MAE) of 1.2097. This underscores the suitability and accuracy of the Aiken-P algorithm for water colour retrieval based on DPC-derived data, highlighting its practical applicability.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call