Phytoplankton biomass and productivity have been continuously monitored from ocean color satellites for over a decade. Yet, the most widely used empirical approach for estimating chlorophyll a (Chl) from satellites can be in error by a factor of 5 or more. Such variability is due to differences in absorption and backscattering properties of phytoplankton and related concentrations of colored-dissolved organic matter (CDOM) and minerals. The empirical algorithms have built-in assumptions that follow the basic precept of biological oceanography—namely, oligotrophic regions with low phytoplankton biomass are populated with small phytoplankton, whereas more productive regions contain larger bloom-forming phytoplankton. With a changing world ocean, phytoplankton composition may shift in response to altered environmental forcing, and CDOM and mineral concentrations may become uncoupled from phytoplankton stocks, creating further uncertainty and error in the empirical approaches. Hence, caution is warranted when using empirically derived Chl to infer climate-related changes in ocean biology. The Southern Ocean is already experiencing climatic shifts and shows substantial errors in satellite-derived Chl for different phytoplankton assemblages. Accurate global assessments of phytoplankton will require improved technology and modeling, enhanced field observations, and ongoing validation of our “eyes in space.”

Using field measurements and quantitative modeling, we demonstrate that red coloration of the sea surface is not associated with any particular group of phytoplankton and is strongly dependent on the physiology of the human visual system. Red or brown surface waters can be produced by high concentrations of most types of algae, colored dissolved organic matter, or suspended sediment. Even though light reflected by red tides commonly peaks in the yellow spectral region (570‐580 nm), human color perception requires consideration of the entire spectrum of light relative to receptors within the human eye. The color shift from green to red is not due to any special optical properties of the algae but results from an overlap in spectral response of the eye’s red and green cones (centered at 564 and 534 nm, respectively). The spectral peak in light reflected from dense algal blooms coincides with a critical hinge point in color vision (570‐580 nm), where fine‐scale shifts in the spectral shape of water‐leaving radiance due to algal absorption and backscattering properties lead to pronounced variations in the observed color. Of the taxa considered, only Chlorophytes and Prochlorophytes lacked sufficient accessory pigments to produce a red tide. Chlorophyll fluorescence and enhanced near‐infrared reflectance (the “red edge”) contribute negligibly to the perceived color. Black water events are produced when water is highly absorbing but lacks backscattering constituents.

Intensifying pressure on global aquatic resources and services due to population growth and climate change is inspiring new surveying technologies to provide science-based information in support of management and policy strategies. One area of rapid development is hyperspectral remote sensing: imaging across the full spectrum of visible and infrared light. Hyperspectral imagery contains more environmentally meaningful information than panchromatic or multispectral imagery and is poised to provide new applications relevant to society, including assessments of aquatic biodiversity, habitats, water quality, and natural and anthropogenic hazards. To aid in these advances, we provide resources relevant to hyperspectral remote sensing in terms of providing the latest reviews, databases, and software available for practitioners in the field. We highlight recent advances in sensor design, modes of deployment, and image analysis techniques that are becoming more widely available to environmental researchers and resource managers alike. Systems recently deployed on space- and airborne platforms are presented, as well as future missions and advances in unoccupied aerial systems (UAS) and autonomous in-water survey methods. These systems will greatly enhance the ability to collect interdisciplinary observations on-demand and in previously inaccessible environments. Looking forward, advances in sensor miniaturization are discussed alongside the incorporation of citizen science, moving toward open and FAIR (findable, accessible, interoperable, and reusable) data. Advances in machine learning and cloud computing allow for exploitation of the full electromagnetic spectrum, and better bridging across the larger scientific community that also includes biogeochemical modelers and climate scientists. These advances will place sophisticated remote sensing capabilities into the hands of individual users and provide on-demand imagery tailored to research and management requirements, as well as provide critical input to marine and climate forecasting systems. The next decade of hyperspectral aquatic remote sensing is on the cusp of revolutionizing the way we assess and monitor aquatic environments and detect changes relevant to global communities.

Within the next decade, NASA plans to launch three new missions with imaging spectrometers for aquatic science and applications: Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) in 2024, Geostationary Littoral Imaging Radiometer (GLIMR) in 2026, and Surface Biology and Geology (SBG) in 2028. Taken together, these missions will evaluate long‐term trends in phytoplankton biomass linked to climate change, and provide new spectral capabilities to assess aquatic biogeochemistry, biophysics, and habitats. Hyperspectral measurements of ocean color, paired with advanced retrieval algorithms, can provide new information on phytoplankton community composition and water quality. We compare the mission architecture and sensor characteristics to identify the synergistic opportunities to merge algorithms, field data, and calibration and validation techniques. Each mission has unique temporal and spatial characteristics to monitor the aquatic transitions from watershed to open ocean ecosystems. SBG provides observations at high spatial scales to monitor emergent, floating, submerged, and benthic habitats from inland to coastal waters. With global daily coverage, PACE can track the fate of material as it meanders offshore and provides an enhanced context for phytoplankton diversity and global biogeochemical cycling. GLIMR is optimized to resolve temporal processes that give rise to aquatic rates and fluxes including phytoplankton growth rates, physiology, and episodic events such as storms. Applications with high spectral, spatial, and temporal resolution from these NASA missions include assessing carbon dynamics and biogeochemical cycling across the land‐ocean continuum, harmful algal blooms, and oil spills.

Significance: Many different types of plankton bloom in the coastal ocean. Some produce harmful toxins, whereas others are considered important contributors to primary production and ecosystem dynamics. Routine ocean color sensors can reveal a dense bloom or “red tide” from space but cannot differentiate types of plankton. The Hyperspectral Imager for the Coastal Ocean on the International Space Station allowed for new “hyperspectral” approaches to identify pigments and assess biophysical forcing associated with different blooms. Consistent with field and molecular observations, imagery revealed dense surface patches of Mesodinium rubrum , a ciliate that uses the chloroplasts from its cryptophyte algal prey to photosynthesize. For the first time, to our knowledge, the distribution and abundance were mapped based on the unique yellow fluorescence properties of its signature pigment phycoerythrin.