Ocean water colour retrieval method based on directional polarimetric camera

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.

Keywords:

• Chlorophyll-a concentrations
• retrieval algorithm
• band-ratio
• look-up table
• remote sensing

Acknowledgements

The authors would like to thank the Anhui Institute of Optics and Precision Mechanics, Hefei Institute of Physical Sciences, Chinese Academy of Sciences, for providing the Directional Polarimetric Camera (DPC) data.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Fundamental Research Funds for the Central Universities under Grant [number JZ2024HGTB0194] and National Natural Science Foundation of China [42275144] and HFIPS Director’s Fund under Grant [number YZJJ2024QN10].