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Many existing techniques for estimating the optical properties of a body of water directly from a hyperspectral remote sensing spectrum are based on the idea of ‘spectral matching’ – that is, input...

Here we report progress in the fabrication, calibration, and testing of a compact spectral imaging camera. The camera uses a micro-array of Fabry-Perot etalons bonded directly to a broadband focal plane array sensor. The array of etalons adds negligible size and weight to the system compared to a panchromatic imager. Other recent demonstrations of compact spectral imagers in the visible and near infrared (VNIR) have commonly used arrays of etalons in a single order, thereby reducing the system bandwidth and sensitivity to achieve the required spectral resolution. Here, we demonstrate a camera utilizing multiple etalon orders in a spectral multiplexing scheme known as Multiple Order Staircase Etalon Spectrometry (MOSES). An important characteristic of the MOSES system is that there is a relaxed tradeoff between spectral resolution and sensitivity (or etalon throughput). Unlike single-order etalon techniques, MOSES allows for the reconstruction of the spectrum to the bandwidth limit of the detector and reflecting layers. This is important in coastal environmental sensing, where IR spectral features may be desired at the same time as UV light transmitted through shallow water layers. This VNIR system demonstration indicates the feasibility of MOSES devices in other wavebands.

In previous works, the authors have shown via numerical simulation that sensor noise, even assuming otherwise perfect knowledge of the environment, can cause large scale variations in the retrieval of concentrations of biophysical parameters in a water body, and also investigated methods for using statistical measures (such as the Mahalanobis distance) to help mitigate these issues. In this work, we derive explicit formulas that can be used to estimate how uncertainty in the sensor radiance is propagated to uncertainty in the remote sensing reflectanceRrs(λ), without the need for simulations. In particular, the formulas show that the variation in Rrs(λ)is affected by not only the noise characteristics of the sensor, but also by the conditions (atmospheric parameters, viewing angles, altitude) under which the data is collected. We include validation results for the formulas over a wide range of atmospheric conditions, and show by example how the collection conditions can affect the uncertainty in Rrs(λ).

At the Naval Research Laboratory Optical Sciences and Remote Sensing Divisions, a compact hyperspectral imaging sensor has been in development using a method of multi-order spectroscopy using Fabry-Perot etalon arrays. This has allowed for the first broadband, ultra-compact spectrometer. A prototype hyperspectral imaging system is now in development for use with an unmanned aerial vehicle. This system will be a “push-broom system” that scans ground data line by line in a row of pixels forming the hyperspectral datacube and will be georeferenced onto a Digital Surface Model of the ground with location (latitude, longitude, altitude) and attitude (azimuth, pitch, roll) GPS-INS 6-degree of freedom parameters. These parameters will be collected through the use of a high-end modern smartphone with its GPS, accelerometer, gyroscope, barometric pressure, and digital compass sensors. In this paper, we discuss the various sensors and systems being utilized with a smartphone for use with the hyperspectral imaging sensor in development.

Studies of phytoplankton ecology in Monterey Bay, CA, USA, using the Hyperspectral Imager for the Coastal Ocean (HICO) and other satellite remote sensing and in-situ observations, were presented in [1]. [...]

One of the inherent challenges in remote sensing is the effect of atmospheric gases and particles on the light received by the sensor. The effects of atmospheric interference need to be adequately corrected for in order to retrieve quantitative biophysical information about a water body from the remotely sensed signal. Atmospheric correction of remotely sensed data is more challenging for inland waters than for open ocean waters due to a number of factors. The proximity of inland waters to various terrestrial sources of atmospheric pollution results in a more optically heterogeneous atmosphere, which complicates atmospheric modeling; the signal received at the sensor is often contaminated by contribution from the adjacent land, which is particularly problematic in cases of raised topography surrounding the water body and complicates atmospheric correction; non-negligible reflectance of water in the near-infrared region due to high sediment concentrations in inland waters (from terrestrial sources such as soil erosion, surface runoff from rainfall, and agricultural and industrial discharge) makes it difficult to accurately estimate and remove the effect of atmospheric aerosol scattering on the received signal. In spite of these and other challenges, a few algorithms have been developed and used for atmospheric correction of remotely sensed data from inland waters with reasonable success. This chapter contains a discussion of the main challenges in atmospheric correction for inland waters and brief descriptions of a few existing atmospheric correction algorithms that are suitable for inland waters.

Spectral variability in the visible, near-infrared and shortwave directional reflectance factor of beach sands and freshwater sheet flow is examined using principal component and correlation matrix analysis of in situ measurements. In previous work we concluded that the hyperspectral bidirectional reflectance distribution function (BRDF) of beach sands in the absence of sheet flow exhibit weak spectral variability, the majority of which can be described with three broad spectral bands with wavelength ranges of 350-450 nm, 700-1350 nm, and 1450-2400 nm. 1 Observing sheet flow on sand we find that a thin layer of water enhances reflectance in the specular direction at all wavelengths and that spectral variability may be described using four spectral band regions of 350-450 nm, 500-950 nm, 950-1350 nm, and 1450-2400 nm. Spectral variations are more evident in sand surfaces of greater visual roughness than in smooth surfaces, regardless of sheet flow.

Hyperspectral imagery (HSI) derived from remote sensing can delineate surface properties of substrates such as type, moisture, and grain size. These are critical parameters that determine the substrate bearing strength. Although HSI only sees the surface layer, statistics can be derived that relate surface properties to the likely bearing strength of soils in particular regions. This information can be used to provide an initial map estimate on large scales of potential bearing strength. We describe an initial validation study at the Virginia Coast Reserve relating airborne HSI to in situ spectral and geotechnical measurements through a spectral-geotechnical lookup table (LUT).

We focus on the validation of a simplified approach to bathymetry retrieval from hyperspectral imagery (HSI) in the very shallow water limit (less than 1–2 m), where many existing bathymetric LIDAR sensors perform poorly. In this depth regime, near infra-red (NIR) reflectance depends primarily on water depth (water absorption) and bottom type, with suspended constituents playing a secondary role. Our processing framework exploits two optimal regions where a simple model depending on bottom type and water depth can be applied in the very shallow limit. These two optimal spectral regions are at a local maximum in the near infra-red reflectance near 810 nm, corresponding to a local minimum in absorption, and a maximum in the first derivative of the reflectance near 720 nm. These two regions correspond to peaks in spectral correlation with bathymetry at these depths.

Hyperspectral imaging data have been collected with different types of imaging spectrometers from aircraft and satellite platforms since the mid-1980s. Because the solar radiation on the sun-surface-sensor path in the 0.4–2.5 µm visible and near-IR spectral regions is subject to absorption and scattering by atmospheric gases and aerosols, the hyperspectral imaging data contains atmospheric effects. In order to use hyperspectral imaging data for quantitative remote sensing of land surfaces and ocean color, the atmospheric effects must be removed. Over the years, atmospheric correction algorithms have evolved from the earlier empirical line method and the flat field method to more recent methods based on rigorous radiative transfer modeling approaches. Here, a review of hyperspectral atmospheric correction techniques is presented. Issues related to spectral smoothing are discussed. Suggestions for improvements to the present atmospheric correction algorithms, mainly the addition of a module for modeling atmospheric nitrogen dioxide absorption effects in the visible, are given.

In this paper, we examine the accuracy of manifold coordinate representations as a reduced representation of a hyperspectral imagery (HSI) lookup table (LUT) for bathymetry retrieval. We also explore on a more limited basis the potential for using these coordinates for modeling other in water properties. Manifold coordinates are chosen because they are a data-driven intrinsic set of coordinates, which naturally parameterize nonlinearities that are present in HSI of water scenes. The approach is based on the extraction of a reduced dimensionality representation in manifold coordinates of a sufficiently large representative set of HSI. The manifold coordinates are derived from a scalable version of the isometric mapping algorithm. In the present and in our earlier works, these coordinates were used to establish an interpolating LUT for bathymetric retrieval by associating the representative data with ground truth data, in this case from a Light Detection and Ranging (LIDAR) estimate in the representative area. While not the focus of the present paper, the compression of LUTs could also be applied, in principle, to LUTs generated by forward radiative transfer models, and some preliminary work in this regard confirms the potential utility for this application. In this paper, we analyze the approach using data acquired by the Portable Hyperspectral Imager for Low-Light Spectroscopy (PHILLS) hyperspectral camera over the Indian River Lagoon, Florida, in 2004. Within a few months of the PHILLS overflights, Scanning Hydrographic Operational Airborne LIDAR Survey LIDAR data were obtained for a portion of this study area, principally covering the beach zone and, in some instances, portions of contiguous river channels. Results demonstrate that significant compression of the LUTs is possible with little loss in retrieval accuracy.

The present operational atmospheric correction algorithm for multichannel remote sensing of ocean color using imaging data acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) works well over clear ocean but can give incorrect results over brighter coastal waters. This is because: 1) the turbid waters are not dark for the two atmospheric correction channels centered near 0.75 and 0.86 mum; and 2) the ocean color channels (0.488, 0.531, and 0.551 mum) often saturate over bright coastal waters. Here, we describe an atmospheric correction algorithm for multichannel remote sensing of coastal waters. This algorithm is a modification of our previously developed atmospheric correction algorithm for hyperspectral data that uses lookup tables generated with a vector radiative transfer code and multilayered atmospheric models. Aerosol models and optical depths are determined by a spectrum-matching technique utilizing channels located at wavelengths longer than 0.86 mum, where the ocean surface is dark. The aerosol information in the visible spectral region is estimated based on the derived aerosol models and optical depths. Water-leaving radiances in the visible spectral region are obtained by subtracting out the atmospheric path radiances from the satellite-measured total radiances. Applications of the algorithm to two MODIS data sets are presented and compared to field measurements. The water-leaving reflectances retrieved with this algorithm over brighter shallow coastal waters compare closely with those from field measurements. In addition, the retrieved water-leaving reflectances over deeper ocean waters compare well with those derived with the MODIS operational algorithm

The concept of imaging spectrometry, or hyperspectral imaging, is becoming increasingly popular in scientific communities in recent years. Hyperspectral imaging data covering the spectral region between 0.4 and 2.5 μm and collected from aircraft and satellite platforms have been used in the study of the earth's atmosphere, land surface, and ocean color properties, as well as on planetary missions. In order to make such quantitative studies, accurate radiometric and spectral calibrations of hyperspectral imaging data are necessary. Calibration coefficients for all detectors in an imaging spectrometer obtained in a laboratory may need to be adjusted when applied to data obtained from an aircraft or a satellite platform. Shifts in channel center wavelengths and changes in spectral resolution may occur when an instrument is airborne or spaceborne due to vibrations, and to changes in instrument temperature and pressure. In this paper, we describe an algorithm for refining spectral calibrations of imaging spectrometer data using observed features in the data itself. The algorithm is based on spectrum-matching of atmospheric water vapor, oxygen, and carbon dioxide bands, and solar Fraunhofer lines. It has been applied to real data sets acquired with airborne and spaceborne imaging spectrometers.

▪ Abstract Study of radio supernovae over the past 20 years includes two dozen detected objects and more than 100 upper limits. From this work it is possible to identify classes of radio properties, demonstrate conformance to and deviations from existing models, estimate the density and structure of the circumstellar material and, by inference, the evolution of the presupernova stellar wind, and reveal the last stages of stellar evolution before explosion. It is also possible to detect ionized hydrogen along the line of sight, to demonstrate binary properties of the stellar system, and to show clumpiness of the circumstellar material. More speculatively, it may be possible to provide distance estimates to radio supernovae. Over the past four years the afterglow of gamma-ray bursters has occasionally been detected in the radio, as well in other wavelengths bands. In particular, the interesting and unusual gamma-ray burst GRB980425, thought to be related to SN1998bw, is a possible link between supernovae and gamma-ray bursters. Analyzing the extensive radio emission data avaliable for SN1998bw, one can describe its time evolution within the well-established framework available for the analysis of radio emission from supernovae. This allows relatively detailed description of a number of physical properties of the object. The radio emission can best be explained as the interaction of a mildly relativistic (Γ ∼ 1.6) shock with a dense preexplosion stellar wind–established circumstellar medium that is highly structured both azimuthally, in clumps or filaments, and radially, with observed density enhancements. Because of its unusual characteristics for a Type Ib/c supernova, the relation of SN1998bw to GRB980425 is strengthened and suggests that at least some classes of GRBs originate in massive star explosions. Thus, employing the formalism for describing the radio emission from supernovae and following the link through SN1998bw/GRB980425, it is possible to model the gross properties of the radio and optical/infrared emission from the half-dozen GRBs with extensive radio observations. From this we conclude that at least some members of the “slow-soft” class of GRBs can be attributed to the explosion of a massive star in a dense, highly structured circumstellar medium that was presumably established by the preexplosion stellar system.

In past work, we have shown that density effects in hyperspectral bi-directional reflectance function (BRDF) data are consistent in laboratory goniometer data, field goniometer measurements with the NRL Goniometer for Portable Hyperspectral Earth Reflectance (GOPHER), and airborne CASI-1500 hyperspectral imagery. Density effects in granular materials have been described in radiative transfer models and are known, for example, to influence both the overall level of reflectance as well as the size of specific characteristics such as the width of the opposition effect in the BRDF. However, in mineralogically complex sands, such as coastal sands, the relative change in reflectance with density depends on the composite nature of the sand. This paper examines the use of laboratory and field hyperspectral goniometer data and their utility for retrieving sand density from airborne hyperspectral imagery. We focus on limitations of current models to describe density effects in BRDF data acquired in the field, laboratory setting, and from airborne systems.

The unusual supernova SN1998bw, which is thought to be related to the gamma-ray burster GRB980425, is a possible link between the two classes of objects. Analyzing the extensive radio emission data avaliable for SN1998bw, we are able to describe its time evolution within the well established framework available for the analysis of radio emission from supernovae. This then allows description of a number of physical properties of the object. The radio emission can best be explained as interaction of a mildly relativistic (Gamma about 1.6) shock with a dense pre-explosion stellar wind established circumstellar medium (CSM) which is highly structured both azimuthally, in clumps or filaments, and radially, with two observed density enhancements separated by about 3e17 cm. With assumptions as to pre-explosion stellar wind conditions, it is possible to estimate that the progenitor to SN 1998bw had a mass loss rate of about 3.5e-5 solar masses per yr with at least two approximately 30% increases in mass-loss rate; the most recent extending from about 1,600 - 4,700 yr before explosion and the oldest known having occurred, with possibly comparable length, about 12,000 yr before explosion. Because of its unusual characteristics for a Type Ib/c SN, the relation of SN1998bw to GRB980425 is strengthened with consequent improvement in our understanding of these poorly understood objects., Comment: 24 pages, 2 figures, to appear in Astrophysical Journal

Long-term monitoring of the radio emission from supernovae with the Very Large Array (VLA) shows that the radio ``light curves'' evolve in a systematic fashion with a distinct peak flux density (and thus, in combination with a distance, a peak spectral luminosity) at each frequency and a well-defined time from explosion to that peak. Studying these two quantities at 6 cm wavelength, peak spectral luminosity (L_{6 cm peak}) and time after explosion date (t_0) to reach that peak (t_{6 cm peak} - t_0), we find that they appear related. In particular, based on two objects, Type Ib supernovae may be approximate radio ``standard candles'' with a 6 cm peak luminosity L_{6 cm peak} \approx 19.9 X 10^{26} erg s^{-1} Hz^{-1}; also based on two objects, Type Ic supernovae may be approximate radio ``standard candles'' with a 6 cm peak luminosity L_{6 cm peak} \approx 6.5 X 10^{26} erg s^{-1} Hz^{-1}; and, based on twelve objects, Type II supernovae appear to obey a relation L_{6 cm peak} \simeq 5.5 X 10^{23} (t_{6 cm peak} - t_0)^{1.4} erg s^{-1} Hz^{-1}, with time measured in days. If these relations are supported by further observations, they provide a means for determining distances to supernovae, and thus to their parent galaxies, from purely radio continuum observations., 31 pages, including 3 PostScript figures. To appear in the Astrophysical Journal (1998 June 10 issue)

Observations of SN 1985L in NGC 5033 with the Very Large Array radio telescope have resulted in two detections of radio emission at 6 cm wavelength about 8 and 16 months after optical discovery. Combined with a number of upper limits and a study of possible models, these indicate that SN 1985L was probably a fairly normal Type II-L radio supernova, somewhat intermediate in radio properties between the well-studied radio supernovae SN 1979C and SN 1980K. A possible late-time optical detection, discussed in an accompanying paper by Fesen (1998), continues the observed correlation between radio and late-time optical emission.

A reanalysis of the radio data for the supernova (SN) 1978K from Ryder et al. clearly shows the expected early-time radio flux density evolution that is characteristic of normal Type II supernovae. However, for the first time ever seen in a radio supernova, the data indicate the need for a time-independent, free-free absorption component along the line of sight. We interpret this constant absorption term as indicative of the presence of an H II region along the line of sight to SN 1978K. More speculatively, this could represent a part of an region associated with the progenitor of SN 1978K. From the available optical and radio data, it is possible not only to describe the characteristics of the circumstellar medium around SN 1978K giving rise to its radio emission, but also to estimate the properties for this intervening H II region. It thus appears that low-frequency observations of radio supernovae at late times may aid in the detection of H II regions along the line of sight, possibly related to the presupernova star's formation environment.

Radio observations of SN 1986E have shown a clear detection of emission at 6 cm wavelength about 8 months after optical discovery. Combined with a number of new upper limits and a study of the possible models, it appears that SN 1986E was probably a fairly normal Type IIL supernova, somewhat similar to SN 1980K, with radio emission at roughly expected levels. This detection continues the correlation between radio detection and late time optical emission., 14 pages, LaTeX (AASTeX), 2 PostScript figures, to appear in ApJ (Letters)

This paper describes a portable hyperspectral goniometer system for measurement of hemispherical conical reflectance factor (HCRF) data for terrestrial applications, especially in the coastal zone. This system, the Goniometer for Portable Hyperspectral Earth Reflectance (GOPHER), consists of a computer-controlled Spectra Vista Corporation HR-1024 full-range spectrometer mounted on a rotating arc and track assembly, allowing complete coverage in zenith and azimuth of a full hemisphere for recording HCRF. The control software allows customized scan patterns to be quickly modified in the field, providing for flexibility in recording HCRF and the opposition effect with varying grid sizes and scan ranges in both azimuth and zenith directions. The spectrometer track can be raised and lowered on a mast to accommodate variations in terrain and land cover. To minimize the effect of variations in illumination during GOPHER scan cycles, a dual-spectrometer approach has been adapted to link records of irradiance recorded by a second spectrometer during the GOPHER HCRF scan cycle. Examples of field data illustrate the utility of the instrument for coastal studies.

This report provides details of a new hyperspectral exploitation tool for developing trafficability special maps from hyperspectral imagery. This new tool, known as the NRL Hyperspectral Imagery Trafficability Tool (HITT), is packaged as a plug-in to the commercial software package ENVI/IDL. HITT is one of several tools being developed and validated by NRL to support coastal characterization from spectral region imagery. This report provides a step-by-step description of the operation of HITT, working through specific examples that begin with a hyperspectral data cube and end with a special map of estimated trafficability in a coastal region. The basis of this new product is a set of spectral-geotechnical libraries and models developed during remote sensing and calibration/validation campaigns conducted by NRL and collaborating institutions in four different coastal types.

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.

In June 2011, a multi-sensor airborne remote sensing campaign was flown at the Virginia Coast Reserve Long Term Ecological Research site with coordinated ground and water calibration and validation (cal/val) measurements. Remote sensing imagery acquired during the ten day exercise included hyperspectral imagery (CASI-1500), topographic LiDAR, and thermal infra-red imagery, all simultaneously from the same aircraft. Airborne synthetic aperture radar (SAR) data acquisition for a smaller subset of sites occurred in September 2011 (VCR'11). Focus areas for VCR'11 were properties of beaches and tidal flats and barrier island vegetation and, in the water column, shallow water bathymetry. On land, cal/val emphasized tidal flat and beach grain size distributions, density, moisture content, and other geotechnical properties such as shear and bearing strength (dynamic deflection modulus), which were related to hyperspectral BRDF measurements taken with the new NRL Goniometer for Outdoor Portable Hyperspectral Earth Reflectance (GOPHER). This builds on our earlier work at this site in 2007 related to beach properties and shallow water bathymetry. A priority for VCR'11 was to collect and model relationships between hyperspectral imagery, acquired from the aircraft at a variety of different phase angles, and geotechnical properties of beaches and tidal flats. One aspect of this effort was a demonstration that sand density differences are observable and consistent in reflectance spectra from GOPHER data, in CASI hyperspectral imagery, as well as in hyperspectral goniometer measurements conducted in our laboratory after VCR'11.

This report describes the data collected during one of a series of Naval Research Laboratory (NRL) remote sensing and calibration and validation (Cal/Val) campaigns, providing data and information for the development of models of coast types and their associated environmental factors. Models allow rapid processing of hyperspectral imagery (HSI), generating shallow water bathymetric charts and trafficability maps. Cal/Val data collected during the Mariana Islands Hyperspectral Airborne Remote Environmental Sensing 2010 (MIHARES 2010) campaign focused on spectral and geotechnical library development, bathymetry, and location of WWII remnant hazards on Pagan, Tinian, and Guam. Ground control data collected during the remote sensing experiment will be useful in building digital elevation models and maps for remote areas such as Pagan, a volcanic island in the Commonwealth of the Northern Mariana Islands (CNMI). Surveyed calibration panels, WWII relics, and underwater panels are all useful in developing anomaly detection algorithms. The primary purpose of this memorandum report is to summarize imagery collections and all Cal/Val data and the project geodatabase, with products described in future publications.

This report describes the data collected during one of a series of NRL remote sensing and calibration and validation (Cal/Val) campaigns, providing data and information for the development of models of coast types and their associated environmental factors for use in rapidly processing hyperspectral imagery (HSI) and generating shallow water bathymetric charts and trafficability maps. This report documents data that was collected during a remote sensing campaign that was conducted from May 18 to 29, 2009 at the Shoalwater Bay Training Area (SWBTA) located in Australia along a tropical stretch of the Queensland coast. Airborne collections from the HyMap (trademark) sensor were used to build shallow water bathymetric charts and trafficability maps that were provided to military planners during Exercise Talisman-Saber 2009, which was conducted primarily in Australia and surrounding waters from July 13 to 16, 2009. This report details both the airborne HyMap imagery collected as well as the ground and water spectral and geotechnical data collected to calibrate and validate the products developed in support of the exercise.

This report describes data collected during one of a series of NRL remote sensing and calibration and validation (Cal/Val) campaigns, undertaken to develop models of coastal environments for use in rapidly processing hyperspectral imagery (HSI) and generating shallow water bathymetric charts and trafficability maps. This report describes data collected during the Hawaii-Hyperspectral Airborne Remote Environmental Sensing (HIHARES'09) experiment conducted at Marine Corps Base Hawaii and Marine Corps Training Area-Bellows from January 21 to February 6, 2009. Airborne HSI from the HyMap(TM) sensor was collected over these sites and adjacent areas in conjunction with NRL Cal/Val activities that sampled spectral and geotechnical data for the development and validation of trafficability, shallow water bathymetry, and vegetation maps appropriate to this coralline coast type. Trafficability maps and shallow water bathymetry maps were derived for HIHARES'09 study sites preparatory to an experiment at Shoalwater Bay, Australia, to support the development of imagery-derived trafficability maps for exercise TALISMAN SABER '09.

This report describes data collected during the first of a series of NRL remote sensing and calibration and validation (Cal/Val) campaigns undertaken to develop models of coastal environments for use in rapidly processing hyperspectral imagery (HSI) and generating shallow water bathymetric charts and trafficability maps. This report documents airborne HSI and sea and ground truth observations made at the Virginia Coast Reserve Long Term Ecological Research (VCR LTER) site during August 15-16, 2007 and September 4-21, 2007. Airborne imagery was obtained from three NRL sensors, two hyperspectral and one thermal. Coordinated water and land spectral and geotechnical Cal/Val data were taken across multiple sites along the VCR barrier island chain from Smith Island to Parramore Island, as well as at several coastal mainland sites along VCR shallow bays, and at sites further north near Chincoteague Island. Cal/Val data supported the development of a first-of-a kind trafficability map derived from HSI, as well as shallow water bathymetry products, all of which were presented at a sponsor demonstration day at the conclusion of the experiment.

At the foundation of the quest to discover the properties of our universe are reliable measurements of distance. We focus on the expanding photosphere method as applied to type II supernovae, indicating how its independent observational tests strengthen our understanding of and confidence in this probe. In keeping with the spirit of this conference, we illustrate some analogies between “freeze-out” of abundances in cosmological or explosive nucleosynthesis and the formation of the spectral luminosity of the supernova. The results of the first critical test of this method, measurement of the distance to supernova 1987A in the Large Magellanic Cloud, are summarized. Plans for use of the Hubble Space Telescope to contribute to an independent direct determination of the Hubble constant are outlined, and prospects for extensions to higher redshifts are discussed.

Over the past three years, the Naval Research Laboratory has conducted three remote sensing campaigns in regions which included barrier island, coral, and mangrove coastal characteristics. These investigations were conducted at the Virginia Coast Reserve during September 2007, in and around Kaneohe and Waimanalo Bays during January and February 2009, and along the Queensland coast in Australia during May 2009. During each of the studies, hyperspectral imagery (HSI) was acquired over the site in conjunction with both land and water spectral and geotechnical measurements. For coastal classification, such as retrievals of bottom reflectance, bathymetry, beach composition, and vegetation type, subtle variations in spectral properties of physical and biological features are often significant. Beach composition in these coast types differed dramatically due to the origin of the sands. These findings suggest the need to develop models specific to a particular coast type.

The design and early results of the Hyperspectral Imager for the Coastal Ocean (HICO) are presented. The performance requirements imposed on the sensor to measure the low signals and to differentiate the optically complex spectra of the coastal ocean are discussed. It is shown the as-built sensor meets or exceeds the design parameters. Further, environmental products from early retrievals of the HICO imagery are presented.

Coastal mapping products and models from hyperspectral remote sensing experiments in different coastal types are compared: barrier island coast (Virginia, 2007), coral coast (Hawaii 2009), mangrove coast (Australia, 2009), and coral limestone and volcanic coasts (Guam and CNMI, 2010). Article not available.

Atmospheric correction of remote sensing imagery of littoral areas is challenging for numerous reasons. This presentation will include a review of these challenges, as well as a review of several proposed solutions. Article not available.

Leaf and canopy level reflectance have been measured by us in an ongoing effort to characterize coastal vegetation in a variety of coastal types. We compare results of these efforts for coastal vegetation mapping. Article not available.