Capabilities of PACE Ocean color Instrument (OCI) for phytoplankton pigments of inland lakes

• First evaluation of PACE OCI bio-optical products in inland lakes. • ACOLITE-DSF provides better R rs accuracy than NASA’s MBAC algorithm. • MDN outperforms empirical/semi-analytical algorithms for lake pigment retrieval. • Inland water-specific algorithms are essential for PACE OCI utility. The Ocean Color Instrument (OCI) onboard PACE satellite, launched in February 2024, provides continuous hyperspectral measurements from 340–890 nm at ∼ 2.5 nm resolution and nine shortwave infrared bands, with ∼ 1 km spatial resolution. While OCI products have been evaluated over ocean and coastal waters, their performance in inland lakes remains unknown. Here, we assessed the capability of state-of-the-art algorithms to retrieve remote sensing reflectance ( R rs ), phytoplankton absorption [ a ph (λ)], and pigment concentrations from OCI hyperspectral imagery. Overall, OCI-derived R rs retrievals have perform unsatisfactory accuracy for these optically complex inland lakes, with ACOLITE-DSF (mean absolute percentage error [MAPE] > 25%) outperforming the NASA’s MBAC algorithm (MAPE > 40%). Errors were lower in the red and green regions and increased toward the blue and near-infrared. Likewise, a ph (λ) retrievals exhibit low accuracy (error > 35%) across all spectral wavelengths, with the Mixtured Density Network (MDN) model (MAPE > 35%) outperforming the semi-analytical Quasi Analytical Algorithm (QAA-750E) (MAPE > 70%). Errors for a ph (λ) were generally lower in the red bands than in the blue and green bands. In addition, MDN-estimated chlorophyll-a and phycocyanin show MAPE values of 68.73% and 88.73%, respectively, which is superior to existing empirical algorithms on this dataset. Overall, while OCI’s hyperspectral measurements show potential for resolving phytoplankton optical features in inland lakes, this capability is limited by the performance of current atmospheric correction (AC) and a ph -retrieval algorithms. Continued development of inland water-specific AC schemes and robust hyperspectral inversion algorithms is therefore essential.