Fraunhofer lines and atmospheric absorption bands interfere with the spectral location of absorption bands of photosynthetic pigments in plankton. Hyperspectral data were used to address this interference on identifying absorption bands by applying derivative analysis of radiance spectra. Algal blooms show elevated radiance data even at longer wavelengths compared to oligotrophic water and may reach radiance values of around 800 W/m2/micrometer/sr at a wavelength of about 0.8 μm. Therefore, the use of a spectral range beyond 0.55 μm is useful to describe bloom characteristics. In particular, the slope between 0.55 μm to 0.80 μm shows an advantage to depict gradients in plankton blooms. Radiance spectra in the region from 0.4 to 0.8 μm for oligotrophic water and near coastal water show similar location of absorption bands when analyzed with derivative analysis but with different amplitudes. For this reason, radiance spectra were also analyzed without atmospheric correction, and various approaches to interpret radiance data over plankton blooms were investigated. Cluster analysis and ratio techniques at longer wavelengths were found to assist in the separation of ocean color gradients and distinguish bio-geochemical provinces in near-coastal waters. Furthermore, using the slope of spectra from plankton blooms, in connection with scatter diagrams at various wavelengths, shows that details can be revealed that would not be recognized in single channels at lower wavelength.

The Hyperspectral Imager for the Coastal Ocean (HICO™), launched to the International Space Station in September 2009, is the first spaceborne hyperspectral imager optimized for environmental characterization of the coastal ocean. Building on the heritage of airborne hyperspectral imagers, HICO™ combines high signal-to-noise ratio, contiguous 10 nm wide spectral channels over the range 400 to 900 nm, and a scene size of 42 × 190 km to capture the scale of coastal dynamics. HICO™ image data is being exploited to produce maps of coastal ocean properties including bathymetry, in-water suspended and dissolved matter, and bottom characteristics, offering a new remote sensing capability for coastal environments worldwide. In this paper we discuss the development and performance characteristics of the HICO™ imager, and present example HICO™ data products.

The laboratory characterization of the optical and radiometric properties of the Hyperspectral Imager for the Coastal Ocean (HICO) is presented. It is shown the as-built sensor meets or exceeds the design parameters necessary to meet the stringent requirements imposed by maritime hyperspectral imaging. The results confirm that in general, the design parameters have been satisfied and the measured system response and signal to noise ratio is shown to match the sensor model. The results are discussed.

We present the results of a study of optical scattering and backscattering of particulates for three coastal sites that represent a wide range of optical properties that are found in U.S. near-shore waters. The 6000 scattering and backscattering spectra collected for this study can be well approximated by a power-law function of wavelength. The power-law exponent for particulate scattering changes dramatically from site to site (and within each site) compared with particulate backscattering where all the spectra, except possibly the very clearest waters, cluster around a single wavelength power-law exponent of -0.94. The particulate backscattering-to-scattering ratio (the backscattering ratio) displays a wide range in wavelength dependence. This result is not consistent with scattering models that describe the bulk composition of water as a uniform mix of homogeneous spherical particles with a Junge-like power-law distribution over all particle sizes. Simultaneous particulate organic matter (POM) and particulate inorganic matter (PIM) measurements are available for some of our optical measurements, and site-averaged POM and PIM mass-specific cross sections for scattering and backscattering can be derived. Cross sections for organic and inorganic material differ at each site, and the relative contribution of organic and inorganic material to scattering and backscattering depends differently at each site on the relative amount of material that is present.

The ability to understand the biogeophysical parameters that create ocean color in coastal waters is fundamental to exploiting remote sensing for coastal applications. The apparent color, which is the upwelling radiance of large water bodies is determined by the absorption and scattering of light caused by the water, the organic and inorganic material contained in the water, and the bottom, when the albedo is high enough and the water is shallow enough.Bio‐optical oceanography measures and models the interaction of the light field with the biological and nonbiological constituents of natural waters. One goal of optical oceanography is to be able to use measured radiance to identify and quantify water constituents, referred to as inherent optical properties (IOPs). Linking optical properties with measured water quality parameters often is made through radiative transfer models, in which the light field is modeled through the water and all of its constituents. This modeling is done to evaluate optical closure, which is the ability to accurately predict the upwelling radiance resulting from a known set of constituents.

This paper demonstrates the characterization of the water properties, bathymetry, and bottom type of the Indian River Lagoon (IRL) on the eastern coast of Florida using hyperspectral imagery. Images of this region were collected from an aircraft in July 2004 using the Portable Hyperspectral Imager for Low Light Spectroscopy (PHILLS). PHILLS is a Visible Near InfraRed (VNIR) spectrometer that was operated at an altitude of 3000 m providing 4 m resolution with 128 bands from 400 to 1000 nm. The IRL is a well studied water body that receives fresh water drainage from the Florida Everglades and also tidal driven flushing of ocean water through several outlets in the barrier islands. Ground truth measurements of the bathymetry of IRL were acquired from recent sonar and LIDAR bathymetry maps as well as water quality studies concurrent to the hyperspectral data collections. From these measurements, bottom types are known to include sea grass, various algae, and a gray mud with water depths less than 6 m over most of the lagoon. Suspended sediments are significant (~35 mg/m3) with chlorophyll levels less than 10 mg/m3 while the absorption due to Colored Dissolved Organic Matter (CDOM) is less than 1 m-1 at 440 nm. Hyperspectral data were atmospherically corrected using an NRL software package called Tafkaa and then subjected to a Look-Up Table (LUT) approach which matches hyperspectral data to calculated spectra with known values for bathymetry, suspended sediments, chlorophyll, CDOM, and bottom type.

: The Portable Hyperspectral Imager for Low-Light Spectroscopy (PHILLS) is a hyperspectral imager specifically designed for imaging the coast ocean. It was deployed at LEO-15 during July 22 through August 2, 2001. This report describes the LEO-15 2001 PHILLS-1 data that were collected and how they were processed to obtain calibrated and atmospherically corrected remote sensing reflectance images. This includes descriptions of laboratory spectral and radiance calibration procedures, how laboratory calibrations are adjusted to match field collected data, and how the data can then be atmospherically corrected and georectified.

The complexity of the coastal ocean, particularly when the bottom is visible, necessitates the use of hyperspectral imagery for remote measurement of bathymetry, bottom type, and water properties. This is in contrast to the open ocean where water column properties alone are of interest and for which the use of multispectral imagery is normally sufficient. The Remote Sensing Division of the NRL has had a program to develop hyperspectral imagery for coastal studies for more than 10 years. The Ocean Portable Hyperspectral Imager for Low-Light Spectroscopy (Ocean PHILLS), the most recent version of NRL's imaging spectrometer, is designed specifically for this application. It uses a thinned, backside-illuminated CCD for high sensitivity and an all-reflective spectrograph with a convex grating in an Offner configuration to produce a nearly distortion-free image. The sensors, which are constructed entirely from commercially available components, have been successfully deployed on numerous aircraft based experiments since 1999. After data collection is complete the data are geolocated, calibrated, atmospherically corrected and used for a variety of ocean and land products. In this presentation, we describe the instrument design, with emphasis on the specifications required for observing the coastal ocean. We also present examples of remote-sensing reflectance data obtained from the LEO-15 site in New Jersey that agree well with ground-truth measurements

We present an overview of the Naval EarthMap Observer (NEMO) spacecraft and then focus on the processing of NEMO data both on-board the spacecraft and on the ground. The NEMO spacecraft provides for Joint Naval needs and demonstrates the use of hyperspectral imagery for the characterization of the littoral environment and for littoral ocean model development. NEMO is being funded jointly by the US government and commercial partners. The Coastal Ocean Imaging Spectrometer (COIS) is the primary instrument on the NEMO and covers the spectral range from 400 to 2500 nm at 10-nm resolution with either 30 or 60 m GSD. The hyperspectral data is processed on-board the NEMO using NRL's Optical Real-time Automated Spectral Identification System (ORASIS) algorithm that provides for real time analysis, feature extraction and greater than 10:1 data compression. The high compression factor allows for ground coverage of greater than 10(6) km(2)/day. Calibration of the sensor is done with a combination of moon imaging, using an onboard light source and vicarious calibration using a number of earth sites being monitored for that purpose. The data will be atmospherically corrected using ATREM. Algorithms will also be available to determine water clarity, bathymetry and bottom type.

A wide variety of applications of imaging spectrometry have been demonstrated using data from aircraft systems. Based on this experience the Navy is pursuing the Hyperspectral Remote Sensing Technology (HRST) Program to use hyperspectral imagery to characterize the littoral environment, for scientific and environmental studies and to meet Naval needs. To obtain the required space based hyperspectral imagery the Navy has joined in a partnership with industry to build and fly the Naval EarthMap Observer(NEMO). The NEMO spacecraft has the Coastal Ocean Imaging Spectrometer (COIS) a hyperspectral imager with adequate spectral and spatial resolution and a high signal-to-noise ratio to provide long term monitoring and real-time characterization of the coastal environment. It includes on-board processing for rapid data analysis and data compression, a large volume recorder, and high speed downlink to handle the required large volumes of data. This paper describes the algorithms for processing the COIS data to provide at-launch ocean data products, and the research and modeling that are planned to use COIS data to advance our understanding of the dynamics of the coastal ocean.

A wide variety of applications of imaging spectrometry have been demonstrated using data from aircraft systems. Based on this experience the Navy is pursuing the Hyperspectral Remote Sensing Technology (HRST) Program to use hyperspectral imagery to characterize the littoral environment, for scientific and environmental studies and to meet Naval needs. To obtain the required space based hyperspectral imagery the Navy has joined in a partnership with industry to build and fly the Naval EarthMap Observer (NEMO). The NEMO spacecraft has the Coastal Ocean Imaging Spectrometer (COIS) a hyperspectral imager with adequate spectral and spatial resolution and a high signal-to- noise ratio to provide long term monitoring and real-time characterization of the coastal environment. It includes on- board processing for rapid data analysis and data compression, a large volume recorder, and high speed downlink to handle the required large volumes of data. This paper describes the algorithms for processing the COIS data to provide at-launch ocean data products and the research and modeling that are planned to use COIS data to advance our understanding of the dynamics of the coastal ocean.

Data centers world-wide are currently addressing the problems associated with the maintenance, access, and analysis of geophysical and celestial databases. One approach has been to focus on the use of visualization techniques to parse and display data, thus allowing for a reduction in the overall time spent in the analysis process. Metadata (information about data) management and visualization techniques are both important elements in this endeavour. Graphical user interface systems, like the Visual Interface for Space and Terrestrial Analysis (VISTA), provide a visually oriented environment that allows for quick and efficient data assessment. The VISTA system attempts to meet the challenge of metadata and data management by providing complete query, visualization, and analysis services.< >

The VISTA system currently under development at the Backgrounds Data Center (BDC) will provide an interactive Graphical User Interface (GUI) to perform queries, visualization and analysis of atmospheric and celestial backgrounds data.The VISTA GUI is designed to provide certain basic services for each scientific database. These are: (1) Specifying data selection conditions and geometry in an interactive graphical fashion; (2) Displaying metadata (information about data) for selected data including spatial, temporal, spectral, and other parameters; (3) Viewing selected data from an ‘Earthview’ (view of the Earth, satellites, and ground‐based observatories) and instrument platform perspective; (4) Displaying the instrument line‐of‐sight field‐of‐view; (5) Retrieving and displaying selected images; (6) Constructing data and image processing tasks via a graphical programming environment, for both interactive and batch processing; (7) Running and diplaying results of independent phenomenology and sensor models; (8) Allowing for direct interactive data analysis and processing through the use of IDL, IRAF, and other scientific analysis tools.The VISTA software system is being developed in ‘C’ and will utilize a number of tools to leverage the development effort. VISTA will have a MOTIF (X protocol) based interface developed with the UIM/X toolkit, 2‐D, and 3‐D graphics displays generated by both UIM/X and the GL graphics language, data and session management via a relational DBMS, and a data pipeline management system. The main goal of the VISTA development is to build a modular framework so that additional computational algorithms, image processing packages, and in‐house data models can be added or withdrawn without loss of functionality.Overal, VISTA operates as the front‐end for the selection, correlation, and manipulation of scientific data, both textual and graphical. The scientific benefits are best respresented by the fact that the user can visually query databases, view physical representations of resulting data, and interactively manipulate and analyze data items, all from a single, integrated GUI.

During the Hyperspectral Coastal Ocean Dynamics Experiment (HyCODE) conducted at Tuckerton, New Jersey near coincident PHILLS airborne hyperspectral data at 1.8 m and 9 m Ground Sample Distance (GSD), AVIRIS data at 20 m GSD and SeaWiFS and MODIS data at 1 km GSD were all collected during a 2 hour time window on July 31, 2001. At the same time 5 research vessels, CODAR, and a variety of in-situ autonomous systems were sampling the environment. This unprecedented data set makes it possible to evaluate the utility of high spectral and spatial resolution data for a variety of coastal environments, and to directly compare it to ocean color measurements from SeaWiFS and MODIS and ship measurements. The offshore end of the study area is a typical continental shelf environment, which is well sampled by the 1 km GSD systems. The inshore end is far more complex and includes salt marshes, barrier islands and complex bottom features in the Mullica River Estuary and Barnegat Bay. This is a preliminary look at these data sets, highlighting the advantages and disadvantages of the different remote sensing data sets for the diversity of environments sampled in this experiment.