ALBERT

Description: Limnology and Oceanography, Page 89-90, February 2019.

Description: The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration 〈2%, relative calibration of 0.2%, polarization sensitivity 〈1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.

Description: Gaussian decomposition and Singular Value Decomposition combined with Non-Negative Least Squares (SVD-NNLS) method are compared and combined to estimate the concentration of 18 phytoplankton pigments (names and abbreviations are displayed in Table 2) from phytoplankton absorption spectra. Results show that both methods tend to overestimate pigment concentration. Gaussian decomposition method provides robust estimation of TChl-a, TChl-b, Chl-c1/2, PSC and PPC. The estimates of TChl-a, Fuco, Diato, $\beta$-Caro, Prasino, TChl-b, Zea, Viola and Lut from SVD-NNLS show reasonable estimation accuracy, while the other pigments are subjected to relatively large prediction errors. The estimated pigments concentrations are further exploited based on Diagnostic Pigment Analysis to derive four phytoplankton functional types, i.e. diatoms, prymnesiophytes, green algae and prokaryotes. By the application of these two methods to the particulate absorption spectra collected by underway spectrophotometry during three summer cruises in 2015 - 2017 in the Fram Strait, continuous surface phytoplankton functional types are estimated along the cruise course.