NASA’s EMIT hyperspectral observations of phytoplankton ecology in estuarine waters

NASA’s EMIT hyperspectral spectrometer provides high spectral (∼7.4 nm) and spatial (60 m) resolution, capabilities that have not been routinely applied to water quality monitoring in shallow aquatic systems, where the bio-optical properties are highly complex. In this study, we developed Hyper-MoE-VAE, a deep-learning inversion framework integrating a mixture-of-experts architecture with variational autoencoders for globally applicable hyperspectral water-quality retrievals. The model accommodates diverse water types and addresses one-to-many inversions to retrieve chlorophyll- a (Chl a ) and phytoplankton absorption coefficient ( a phy ) from hyperspectral remote sensing reflectance ( R rs ). Hyper-MoE-VAE was trained on a global bio-optical dataset and applied to EMIT imagery over Lake Pontchartrain. Same-day field matchups acquired on 14 April 2025 provide the first validation of EMIT-derived Chl a (MAPE = 7.66 %; MAE = 1.13 in log 10 space, unitless) and a phy across all EMIT bands, with representative performance (NRMSE = 0.09–0.11 m −1 ; ε = 29–36 %), revealing a muted Chl a response under highly turbid freshwater conditions and a clear shift toward chlorophyte dominance following fresh inputs. In addition, PACE-OCI, also hyperspectral with lower spatial resolution, was compared with EMIT for Chl a retrievals. Both sensors show comparable spatial patterns despite differences in spectral and spatial resolution, supporting the Hyper-MoE-VAE’s cross-mission applicability. These findings demonstrate EMIT’s strong potential for characterizing phytoplankton dynamics, both in abundance and community composition, and for monitoring harmful algal blooms (HABs) in aquatic systems.