Dynamic range and sensitivity requirements of satellite ocean color sensors: learning from the past.

Sensor design and mission planning for satellite ocean color measurements requires careful consideration of the signal dynamic range and sensitivity (specifically here signal-to-noise ratio or SNR) so that small changes of ocean properties (e.g., surface chlorophyll-a concentrations or Chl) can be quantified while most measurements are not saturated. Past and current sensors used different signal levels, formats, and conventions to specify these critical parameters, making it difficult to make cross-sensor comparisons or to establish standards for future sensor design. The goal of this study is to quantify these parameters under uniform conditions for widely used past and current sensors in order to provide a reference for the design of future ocean color radiometers. Using measurements from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite (MODISA) under various solar zenith angles (SZAs), typical (L(typical)) and maximum (L(max)) at-sensor radiances from the visible to the shortwave IR were determined. The L(typical) values at an SZA of 45° were used as constraints to calculate SNRs of 10 multiband sensors at the same L(typical) radiance input and 2 hyperspectral sensors at a similar radiance input. The calculations were based on clear-water scenes with an objective method of selecting pixels with minimal cross-pixel variations to assure target homogeneity. Among the widely used ocean color sensors that have routine global coverage, MODISA ocean bands (1 km) showed 2-4 times higher SNRs than the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) (1 km) and comparable SNRs to the Medium Resolution Imaging Spectrometer (MERIS)-RR (reduced resolution, 1.2 km), leading to different levels of precision in the retrieved Chl data product. MERIS-FR (full resolution, 300 m) showed SNRs lower than MODISA and MERIS-RR with the gain in spatial resolution. SNRs of all MODISA ocean bands and SeaWiFS bands (except the SeaWiFS near-IR bands) exceeded those from prelaunch sensor specifications after adjusting the input radiance to L(typical). The tabulated L(typical), L(max), and SNRs of the various multiband and hyperspectral sensors under the same or similar radiance input provide references to compare sensor performance in product precision and to help design future missions such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission and the Pre-Aerosol-Clouds-Ecosystems (PACE) mission currently being planned by the U.S. National Aeronautics and Space Administration (NASA).

Vicarious calibrations of HICO data acquired from the International Space Station.

The Hyperspectral Imager for the Coastal Ocean (HICO) presently onboard the International Space Station (ISS) is an imaging spectrometer designed for remote sensing of coastal waters. The instrument is not equipped with any onboard spectral and radiometric calibration devices. Here we describe vicarious calibration techniques that have been used in converting the HICO raw digital numbers to calibrated radiances. The spectral calibration is based on matching atmospheric water vapor and oxygen absorption bands and extraterrestrial solar lines. The radiometric calibration is based on comparisons between HICO and the EOS/MODIS data measured over homogeneous desert areas and on spectral reflectance properties of coral reefs and water clouds. Improvements to the present vicarious calibration techniques are possible as we gain more in-depth understanding of the HICO laboratory calibration data and the ISS HICO data in the future.

Optical scattering and backscattering by organic and inorganic particulates in U.S. coastal waters.

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.

Interpretation of hyperspectral remote-sensing imagery by spectrum matching and look-up tables.

A spectrum-matching and look-up-table (LUT) methodology has been developed and evaluated to extract environmental information from remotely sensed hyperspectral imagery. The LUT methodology works as follows. First, a database of remote-sensing reflectance (Rrs) spectra corresponding to various water depths, bottom reflectance spectra, and water-column inherent optical properties (IOPs) is constructed using a special version of the HydroLight radiative transfer numerical model. Second, the measured Rrs spectrum for a particular image pixel is compared with each spectrum in the database, and the closest match to the image spectrum is found using a least-squares minimization. The environmental conditions in nature are then assumed to be the same as the input conditions that generated the closest matching HydroLight-generated database spectrum. The LUT methodology has been evaluated by application to an Ocean Portable Hyperspectral Imaging Low-Light Spectrometer image acquired near Lee Stocking Island, Bahamas, on 17 May 2000. The LUT-retrieved bottom depths were on average within 5% and 0.5 m of independently obtained acoustic depths. The LUT-retrieved bottom classification was in qualitative agreement with diver and video spot classification of bottom types, and the LUT-retrieved IOPs were consistent with IOPs measured at nearby times and locations.

New approach for the radiometric calibration of spectral imaging systems.

The calibration of multispectral and hyperspectral imaging systems is typically done in the laboratory using an integrating sphere, which usually produces a signal that is red rich. Using such a source to calibrate environmental monitoring systems presents some difficulties. Not only is much of the calibration data outside the range and spectral quality of data values that are expected to be captured in the field, using these measurements alone may exaggerate the optical flaws found within the system. Left unaccounted for, these flaws will become embedded in to the calibration, and thus, they will be passed on to the field data when the calibration is applied. To address these issues, we used a series of well-characterized spectral filters within our calibration. It provided us with a set us stable spectral standards to test and account for inadequacies in the spectral and radiometric integrity of the optical imager.

Ocean PHILLS hyperspectral imager: design, characterization, and calibration.

The Ocean Portable Hyperspectral Imager for Low-Light Spectroscopy (Ocean PHILLS) is a hyperspectral imager specifically designed for imaging the coastal ocean. It uses a thinned, backsideilluminated CCD for high sensitivity and an all-reflective spectrograph with a convex grating in an Offner configuration to produce a nearly distortionfree image. The sensor, which was constructed entirely from commercially available components, has been successfully deployed during several oceanographic experiments in 1999-2001. Here we describe the instrument design and present the results of laboratory characterization and calibration. We also present examples of remote-sensing reflectance data obtained from the LEO-15 site in New Jersey that agrees well with ground-truth measurements.

Derivative analysis of absorption features in hyperspectral remote sensing data of carbonate sediments.

This study uses derivative spectroscopy to assess qualitative and quantitative information regarding seafloor types that can be extracted from hyperspectral remote sensing reflectance signals. Carbonate sediments with variable concentrations of microbial pigments were used as a model system. Reflectance signals measured directly over sediment bottoms were compared with remotely sensed data from the same sites collected using an airborne sensor. Absorption features associated with accessory pigments in the sediments were lost to the water column. However major sediment pigments, chlorophyll a and fucoxanthin, were identified in the remote sensing spectra and showed quantitative correlation with sediment pigment concentrations. Derivative spectra were also used to create a simple bathymetric algorithm.