The study of aquatic ecosystems is an important research area addressing diverse problems such as carbon sequestration in coastal margins and wetlands, kelp and seagrass studies, coral reefs, harmful algal blooms and hypoxia, and carbon cycling in this dynamic environment. The application of an imaging spectrometer to aquatic ecosystem study is particularly challenging due to low water-leaving radiance levels adjacent to the shore region with its higher values. The Committee on Earth Observation Satellites (CEOS) has established more stringent performance standards for the visible/near infrared wavelengths than are typically available in imaging spectrometer designs. We have recently developed a compact form imaging spectrometer, the Chrisp Compact VNIR/SWIR Imaging Spectrometer (CCVIS), that facilitates their modular usage with a wide field telescope without sacrificing performance. The CCVIS design and the operational concept have predicted performance that approaches the CEOS standards. The envisioned satellite implementation requires a pitchback maneuver where the imaging of the slit projected onto the surface is slowly scanned while recording focal plane array readouts at a higher rate thereby avoiding saturation over the land surface while obtaining a high signal-to-noise ratio over the water. The effective frame rate is determined by the time it takes to scan the projected slit one ground sample distance (GSD). This approach has the added benefit of measuring a range of angles during a single GSD acquisition, providing insight into the bidirectional reflectance distribution function (BRDF).
Optical imaging of coral reefs and other benthic communities present below one attenuation depth, the limit of effective airborne and satellite remote sensing, requires the use of in situ platforms such as autonomous underwater vehicles (AUVs). The Seabed AUV, which was designed for high-resolution underwater optical and acoustic imaging, was used to characterize several deep insular shelf reefs of Puerto Rico and the US Virgin Islands using digital imagery. The digital photo transects obtained by the Seabed AUV provided quantitative data on living coral, sponge, gorgonian, and macroalgal cover as well as coral species richness and diversity. Rugosity, an index of structural complexity, was derived from the pencil-beam acoustic data. The AUV benthic assessments could provide the required information for selecting unique areas of high coral cover, biodiversity and structural complexity for habitat protection and ecosystem-based management. Data from Seabed sensors and related imaging technologies are being used to conduct multi-beam sonar surveys, 3-D image reconstruction from a single camera, photo mosaicking, image based navigation, and multi-sensor fusion of acoustic and optical data.
Remote sensing is increasingly being used as a tool to quantitatively assess the location, distribution and relative health of coral reefs and other shallow aquatic ecosystems. As the use of this technology continues to grow and the analysis products become more sophisticated, there is an increasing need for comprehensive ground truth data as a means to assess the algorithms being developed. The University of Puerto Rico at Mayaguez (UPRM), one of the core partners in the NSF sponsored Center for Subsurface Sensing and Imaging Systems (CenSSIS), is addressing this need through the development of a fully-characterized field test environment on Enrique Reef in southwestern Puerto Rico. This reef area contains a mixture of benthic habitats, including areas of seagrass, sand, algae and coral, and a range of water depths, from a shallow reef flat to a steeply sloping forereef. The objective behind the test environment is to collect multiple levels of image, field and laboratory data with which to validate physical models, inversion algorithms, feature extraction tools and classification methods for subsurface aquatic sensing. Data collected from Enrique Reef currently includes airborne, satellite and field-level hyperspectral and multispectral images, in situ spectral signatures, water bio-optical properties and information on habitat composition and benthic cover. We present a summary of the latest results from Enrique Reef, discuss our concept of an open testbed for the remote sensing community and solicit other users to utilize the data and participate in ongoing system development.
Benthic habitats are the different bottom environments as defined by distinct physical, geochemical, and biological
characteristics. Remote sensing is increasingly being used to map and monitor the complex dynamics associated with
estuarine and nearshore benthic habitats. Advantages of remote sensing technology include both the qualitative benefits
derived from a visual overview, and more importantly, the quantitative abilities for systematic assessment and
monitoring. Advancements in instrument capabilities and analysis methods are continuing to expand the accuracy and
level of effectiveness of the resulting data products. Hyperspectral sensors in particular are rapidly emerging as a more
complete solution, especially for the analysis of subsurface shallow aquatic systems. The spectral detail offered by
hyperspectral instruments facilitates significant improvements in the capacity to differentiate and classify benthic
habitats. This paper reviews two techniques for mapping shallow coastal ecosystems that both combine the retrieval of
water optical properties with a linear unmixing model to obtain classifications of the seafloor. Example output using
AVIRIS hyperspectral imagery of Kaneohe Bay, Hawaii is employed to demonstrate the application potential of the two
approaches and compare their respective results.
An important step to determine whether certain coastal environment parameters can be estimated from remote sensing measurements is to establish their identifiability from the water leaving remote sensing reflectance. This work addresses the sensitivity analysis of water leaving remote sensing reflectance to water constituents. The model used in the sensitivity analysis is Hydrolight, a radiative transfer code for ocean waters. We use the Morris factor screening method to determine which parameters have a substantial influence on the remote sensing reflectance. From Morris results, we realize a more precise sensitivity analysis focusing on the most influential parameters, using variance decomposition (Sobol method). As an important example of application, we perform a sensitivity analysis of coral reefs in coastal shallow waters, where the concentrations of Chlorophyll, yellow substance and suspended sediments were limited to a feasible range of variability. The results of the sensitivity analysis lead us to the formulation of band relationships for the estimation of water depth and seabed reflectance in coral reefs.
The IAI Network for the measurement of ultraviolet radiation in Chile, Argentina and Puerto Rico is composed of ten multi-channel radiometers (GUV 511, Bisopherical Instruments Inc.), which are periodically sun calibrated with a traveling reference GUV (RGUV). The RGUV is calibrated under solar light against a SUV100 spectroradiometer. This calibration is then transferred to each instrument in the network through the RGUV. A previous multi-regression model proved to be suitable to derive narrowband irradiance from broadband irradiance, ozone column and solar zenith angles (SZA). A recent modification of the existing multi-regression model improved the multi-channel instrument sun calibration against spectroradiometers. In this approach, the narrowband irradiance is the SUV spectral irradiance and the broadband is the multi-channel GUV irradiance. We included the azimuth angle as a parameter into the multi-regression equation and we applied a non-linear function, instead of a single coefficient, to correct for SZA. In this paper, the new multi-regression approach is applied to both steps of a GUV calibration: SUV - RGUV and RGUV - GUV and the results are compared with traditional calibration methods. Important improvements are observed in the calibration, in particular for SZA larger than 50°.
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