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 U.S. 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 work 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<SUP>6</SUP> km<SUP>2</SUP>/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.
The Ocean Portable Hyperspectral Imager for Low-Light spectroscopy (Ocean PHILLS), is a new hyperspectral imager specifically designed for imaging the coastal ocean. 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 distortion free image. Here we describe the instrument design and present the results of laboratory calibration and characterization and example results from a two week field experiment imaging the coastal waters off Lee Stocking, Island, Bahamas.
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.
Airborne hyperspectral and nadir-viewing laser data can be combined to ascertain shallow water bathymetry. The combination emphasizes the advances and overcomes the disadvantages of each method used alone. For laser systems, both the hardware and software for obtaining off-nadir measurement are complicated and expensive, while for the nadir view the conversion of laser pulse travel time to depth is straightforward. The hyperspectral systems can easily collect data in a full swath, but interpretation for water depth requires careful calibration and correction for transmittance through the atmosphere and water. Relative depths are apparent in displays of several subsets of hyperspectral data, for example, single blue-green wavelengths, endmembers that represent the pure water component of the data, or ratios of deep to shallow water endmembers. A relationship between one of these values and the depth measured by the aligned nadir laser can be determined, and then applied to the rest of the swath to obtain depth in physical units for the entire area covered. We demonstrate this technique using bathymetric charts as a proxy for laser data, and hyperspectral data taken by AVIRIS over Lake Tahoe and Key West.
Coordinated flights of two calibrated airborne imaging spectrometers, HYDICE and AVIRIS, were conducted on June 22, 1995 over Lake Tahoe. As part of HYDICE's first operational mission, one objective was to test the system performance over the dark homogeneous target provided by the clear deep waters of the lake. The high altitude and clear atmosphere makes Lake Tahoe a simpler test target than near-shore marine environments, where large aerosols complicate atmospheric correction and sediment runoff and high chlorophyll levels make interpretation of he data difficult. Calibrated data from both runoff and high chlorophyll levels make interpretation of the data difficult. Calibrated data from both sensors was provided in physical units of radiance. The atmospheric radiative transfer code, MODTRAN was used to remove the path radiance between the ground and sensor and the skylight reflected from the water surface. The resulting water-leaving spectrometer, and with values calculated form in-water properties using the HYDROLIGHT radiative transfer code. The agreement of the water-leaving radiance for the HYDICE data, the ground-truth spectral measurements, and the results of the radiative transfer code are excellent for wavelengths greater than 0.45 micrometers . The AVIRIS flight took place more than an hour closer to noon, which makes the radiance measurements not directly comparable. Comparisons to radiative transfer output for this later time indicate that the AVIRIS data is strongly by sun glint. Because water-leaving radiance is dependent upon the characteristics of the water, it can be analyzed for some of those properties. Using the CZCS algorithm based on the water-leaving radiance at two wavelengths, the chlorophyll content of Lake Tahoe was computed from the HYDICE and ground-truth data. Resulting values are slightly higher than measurements made two weeks earlier from water samples, indicating a growth in the phytoplankton population which is very plausible given the intervening atmospheric conditions. The success in determining water-leaving radiance and interpreting it for pigment concentration are very positive results for this early HYDICE flight. The interpretations made so far do not make use of the full spectral content of the data, so much room for advancement remains.
Constrained energy minimization (CEM) has been applied to the mapping of the quantitative areal distribution of the mineral alunite in an approximately 1.8 km<SUP>2</SUP> area of the Cuprite mining district, Nevada. CEM is a powerful technique for rapid quantitative mineral mapping which requires only the spectrum of the mineral to be mapped. A priori knowledge of background spectral signatures is not required. Our investigation applies CEM to calibrated radiance data converted to apparent reflectance (AR) and to single scattering albedo (SSA) spectra. The radiance data were acquired by the 210 channel, 0.4 micrometers to 2.5 micrometers airborne Hyperspectral Digital Imagery Collection Experiment sensor. CEM applied to AR spectra assumes linear mixing of the spectra of the materials exposed at the surface. This assumption is likely invalid as surface materials, which are often mixtures of particulates of different substances, are more properly modeled as intimate mixtures and thus spectral mixing analyses must take account of nonlinear effects. One technique for approximating nonlinear mixing requires the conversion of AR spectra to SSA spectra. The results of CEM applied to SSA spectra are compared to those of CEM applied to AR spectra. The occurrence of alunite is similar though not identical to mineral maps produced with both the SSA and AR spectra. Alunite is slightly more widespread based on processing with the SSA spectra. Further, fractional abundances derived from the SSA spectra are, in general, higher than those derived from AR spectra. Implications for the interpretation of quantitative mineral mapping with hyperspectral remote sensing data are discussed.
The hyperspectral digital imagery collection experiment (HYDICE) sensor records instrument counts for scene data, in-flight spectral and radiometric calibration sequences, and dark current levels onto an AMPEX DCRsi data tape. Following flight, the HYDICE ground data processing subsystem (GDPS) transforms selected scene data from digital numbers (DN) to calibrated radiance levels at the sensor aperture. This processing includes: dark current correction, spectral and radiometric calibration, conversion to radiance, and replacement of bad detector elements. A description of the algorithms for post-flight data processing is presented. A brief analysis of the original radiometric calibration procedure is given, along with a description of the development of the modified procedure currently used. Example data collected during the 1995 flight season, but uncorrected and processed, are shown to demonstrate the removal of apparent sensor artifacts (e.g., non-uniformities in detector response over the array) as a result of this transformation.