Hyperspectral in Situ Support for PACE (Hyperinspace): Autonomous Above-Water Radiometry

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Spatially Resolving Ocean Color and Sediment Dispersion in River Plumes, Coastal Systems, and Continental Shelf Waters

Satellite remote sensing of ocean color in dynamic coastal, inland, and nearshorewaters is impeded by high variability in optical constituents, demands specialized atmospheric correction, and is limited by instrument sensitivity. To accurately detect dispersion of bio-optical properties, remote sensors require ample signal-to-noise ratio (SNR) to sense small variations in ocean color without saturating over bright pixels, an atmospheric correction that can accommodate significantwater-leaving radiance in the near infrared (NIR), and spatial and temporal resolution that coincides with the scales of variability in the environment. Several current and historic space-borne sensors have met these requirements with success in the open ocean, but are not optimized for highly red-reflective and heterogeneous waters such as those found near river outflows or in the presence of sediment resuspension. Here we apply analytical approaches for determining optimal spatial resolution, dominant spatial scales of variability ("patches"), and proportions of patch variability that can be resolved from four river plumes around the world between 2008 and 2011. An offshore region in the Sargasso Sea is analyzed for comparison. A method is presented for processing Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra imagery including cloud detection, stray lightmasking, faulty detector avoidance, and dynamic aerosol correction using short-wave- and near-infrared wavebands in extremely turbid regions which pose distinct optical and technical challenges. Results showthat a pixel size of approx. 520 mor smaller is generally required to resolve spatial heterogeneity in ocean color and total suspended materials in river plumes. Optimal pixel size increases with distance from shore to approx. 630 m in nearshore regions, approx 750 m on the continental shelf, and approx. 1350 m in the open ocean. Greater than 90% of the optical variability within plume regions is resolvable with 500 m resolution, and small, but significant, differences were found between peak and nadir river flow periods in terms of optimal resolution and resolvable proportion of variability

Remote Sensing of CDOM, CDOM Spectral Slope, and Dissolved Organic Carbon in the Global Ocean

A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromophoric Dissolved Organic Matter (CDOM) absorption coefficients from 245715 nm, CDOM spectral slopes in eight visible and ultraviolet wavebands, dissolved and particulate organic carbon (DOC and POC, respectively), and inherent optical, physical, and biogeochemical properties. From field optical and radiometric data and satellite measurements, several semi-analytical, empirical, and machine learning algorithms for retrieving global DOC, CDOM, and CDOM slope were developed, optimized for global retrieval, and validated. Global climatologies of satellite-retrieved CDOM absorption coefficient and spectral slope based on the most robust of these algorithms lag seasonal patterns of phytoplankton biomass belying Case 1 assumptions, and track terrestrial runoff on ocean basin scales. Variability in satellite retrievals of CDOM absorption and spectral slope anomalies are tightly coupled to changes in atmospheric and oceanographic conditions associated with El Nio Southern Oscillation (ENSO), strongly covary with the multivariate ENSO index in a large region of the tropical Pacific, and provide insights into the potential evolution and feedbacks related to sea surface dissolved carbon in a warming climate. Further validation of the DOC algorithm developed here is warranted to better characterize its limitations, particularly in mid-ocean gyres and the southern oceans

Developing Ocean Color Remote Sensing Algorithms for Retrieving Optical Properties and Biogeochemical Parameters in the Optically Complex Waters of Long Island Sound

The optical properties of the sea determine how light penetrates to depth, interacts with water-borne constituents, and re-emerges as scattered rays. By inversion, quantifying change in the spectral light field as it reflects from the sea unlocks information about the water\u27s optical properties, which can then be used to quantify the suspended and dissolved biogeochemical constituents in the water. Retrieving bio-optical properties is relatively straightforward for the open ocean where phytoplankton-derived materials dominate ocean color. In contrast, the presence of land-derived material contributes significantly to the optical signature of nearshore waters, making the development of ocean color algorithms considerably more challenging. A hypothesis of this research is that characterization of the spectral nature of bio-optical properties in these optically complex waters facilitates optimization of semi-analytical algorithms for retrieving these properties. ^ The main goal of this research is to develop an ocean color remote sensing algorithm for the highly turbid, estuarine waters of Long Island Sound (LIS) Bio-optical data collected in LIS showed it to be strongly influenced by the surrounding watershed and characterized by exceptionally high absorption associated with phytoplankton, non-algal particulate material, and chromophoric dissolved material compared to other coastal environments world-wide. Variability in the magnitudes of inherent optical properties, IOPs (e.g. absorption, scattering and attenuation coefficients), is explained by local influences such as major river outflows, as well as seasonal changes. Nevertheless, ocean color parameters describing the spectral shape of IOPs—parameters to which algorithms optimization is sensitive—are fairly constant across the region, possibly a result of the homogenizing influence of vigorous tidal and subtidal mixing or relative regional homogeneity in the biogeochemical nature of terrigenous material. ^ Field observations of IOPs, biogeochemical properties (e.g. chlorophyll concentration and total suspended materials, TSM), and sea-surface reflectances are used to select, optimize and validate an ocean color algorithm for LIS. Optimization revealed that a 640 nm reflectance channel and a spectrally varying f/Q factor (i.e. relating reflectances to IOPs) were critical to good performance. The algorithm is applied—as an example of its utility—to satellite imagery to quantify TSM across the region during record flooding events of March 2010. Analysis shows that the delivery of TSM during these storms was strongly dependent on localized land-use characteristics. ^

Remote Sensing of CDOM, CDOM Spectral Slope, and Dissolved Organic Carbon in the Global Ocean

A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromophoric Dissolved Organic Matter (CDOM) absorption coefficients from 245⁻715 nm, CDOM spectral slopes in eight visible and ultraviolet wavebands, dissolved and particulate organic carbon (DOC and POC, respectively), and inherent optical, physical, and biogeochemical properties. From field optical and radiometric data and satellite measurements, several semi-analytical, empirical, and machine learning algorithms for retrieving global DOC, CDOM, and CDOM slope were developed, optimized for global retrieval, and validated. Global climatologies of satellite-retrieved CDOM absorption coefficient and spectral slope based on the most robust of these algorithms lag seasonal patterns of phytoplankton biomass belying Case 1 assumptions, and track terrestrial runoff on ocean basin scales. Variability in satellite retrievals of CDOM absorption and spectral slope anomalies are tightly coupled to changes in atmospheric and oceanographic conditions associated with El Niño Southern Oscillation (ENSO), strongly covary with the multivariate ENSO index in a large region of the tropical Pacific, and provide insights into the potential evolution and feedbacks related to sea surface dissolved carbon in a warming climate. Further validation of the DOC algorithm developed here is warranted to better characterize its limitations, particularly in mid-ocean gyres and the southern oceans

Aquatic Color Radiometry Remote Sensing of Coastal and Inland Waters: Challenges and Recommendations for Future Satellite Missions

Aquatic color radiometry remote sensing of coastal and inland water bodies is of great interest to a wide variety of research, management, and commercial entities as well as the general public. However, most current satellite radiometers were primarily designed for observing the global ocean and not necessarily for observing coastal and inland waters. Therefore, deriving coastal and inland aquatic applications from existing sensors is challenging. We describe the current and desired state of the science and highlight unresolved issues in four fundamental elements of aquatic satellite remote sensing namely, mission capability, in situ observations, algorithm development, and operational capacity. We discuss solutions, future plans, and recommendations that directly affect the science and societal impact of future missions with capability for observing coastal and inland aquatic systems