Daniel Korwan

Hyperspectral Imager for the Coastal Ocean: instrument description and first images

The Hyperspectral Imager for the Coastal Ocean (HICO) is the first spaceborne hyperspectral sensor designed specifically for the coastal ocean and estuarial, riverine, or other shallow-water areas. The HICO generates hyperspectral images, primarily over the 400-900 nm spectral range, with a ground sample distance of ≈90 m (at nadir) and a high signal-to-noise ratio. The HICO is now operating on the International Space Station (ISS). Its cross-track and along-track fields of view are 42 km (at nadir) and 192 km, respectively, for a total scene area of 8000 km(2). The HICO is an innovative prototype sensor that builds on extensive experience with airborne sensors and makes extensive use of commercial off-the-shelf components to build a space sensor at a small fraction of the usual cost and time. Here we describe the instruments design and characterization and present early images from the ISS.

Cross-Scale Patterns in Shrub Thicket Dynamics in the Virginia Barrier Complex

A bstractTo interpret broad-scale erosion and accretion patterns and the expansion and contraction of shrub thickets in response to sea level rise for a coastal barrier system, we examined the fine-scale processes of shrub recruitment and mortality within the context of the influence of ocean current and sediment transport processes on variations in island size and location. We focused on Myrica cerifera shrub thickets, the dominant woody community on most barrier islands along the coastline of the southeastern USA. Observations suggest that M. cerifera, a salt-intolerant species, is increasing in cover throughout the Virginia barrier islands, yet rising sea level in response to climate change is increasing erosion and reducing island area. Our objective was to explain this apparent paradox using pattern–process relationships across a range of scales with a focus on ocean currents and sediment transport interacting with island characteristics at intermediate scales. Multi-decadal comparisons across scales showed a complex pattern. At the scale of the entire Virginia barrier complex, modest decreases in upland area were accompanied by large increases in shrub area. Responses were more variable for individual islands, reflecting inter-island variations in erosion and accretion due to differences in sediment transport via ocean currents. Several islands underwent dramatic shrub expansion. Only for within-island responses were there similarities in the pattern of change, with a lag-phase after initial shrub colonization followed by development of linear, closed canopy thickets. Understanding the fine-scale processes of shrub seedling establishment and thicket development, in conjunction with the influence of ocean currents and sediment transport, provides a framework for interpreting island accretion and erosion patterns and subsequent effects on shrub thicket expansion or contraction across scales of time and space.

Bathymetric Retrieval From Hyperspectral Imagery Using Manifold Coordinate Representations

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 Hyperspectral Imager for the Coastal Ocean (HICO) on the International Space Station

The HICO (Hyperspectral Imager for the Coastal Ocean) program is the first demonstration of environmental characterization of the coastal zone using a spaceborne maritime hyperspectral imager. HICO is sponsored by the Office of Naval Research as an Innovative Naval Prototype (INP), and will demonstrate coastal products including water clarity, bottom types, bathymetry and on-shore vegetation maps. As an INP, HICO will also demonstrate innovative ways to reduce the cost and schedule of this space mission by adapting proven aircraft imager architecture and using Commercial Off-The-Shelf (COTS) components where possible.

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.

Comparison of spectral radiance calibrations at oceanographic and atmospheric research laboratories

This report describes the first Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Radiometric Intercomparison (SIMRIC-1). The purpose of the SIMRIC-1 is to ensure a common radiometric scale among the calibration facilities that are engaged in calibrating in situ radiometers used for ocean colour-related research and to document the calibration procedures and protocols. SIMBIOS staff visited the seven participating laboratories for at least two days each. The SeaWiFS Transfer Radiometer (SXR-II) measured the calibration radiances produced in the laboratories. The measured radiances were compared with the radiances expected by the laboratories. Typically, the measured radiances were higher than the expected radiances by 0 to 2%. This level of agreement is satisfactory. Several issues were identified where the calibration protocols need to be improved, especially the reflectance calibration of the reference plaques and the distance correction when using the irradiance standards at distances greater than 50?cm. The responsivity of the SXR-II changed from 0.3% (channel 6) to 1.6% (channel 2) from December 2000 to December 2001. Monitoring the SXR-II with a portable light source showed a linear drift of the calibration, except for channel 1, where a 2% drop occurred in summer.

Retrieval of Substrate Bearing Strength from Hyperspectral Imagery during the Virginia Coast Reserve (VCR’07) Multi-Sensor Campaign

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).

Bathymetry Retrieval from Hyperspectral Imagery in the Very Shallow Water Limit: A Case Study from the 2007 Virginia Coast Reserve (VCR'07) Multi-Sensor Campaign

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.

A Technique For Removing Second-Order Light Effects From Hyperspectral Imaging Data

The Hyperspectral Imager for the Coastal Ocean (HICO) instrument currently on board the International Space Station is a new sensor designed specifically for the studies of turbid coastal waters and large inland lakes and rivers. It covers the wavelength range between 0.4 and 0.9 μm with a spectral resolution of 5.7 nm and a spatial resolution of approximately 90 m. The HICO sensor is not equipped with a second-order blocking filter in front of the focal plane array. As a result, the second-order light from the shorter visible spectral region falls onto the detectors covering the near-IR spectral region above 0.8 μm. In order to have accurate radiometric calibration of the near-IR channels, the second-order light contribution needs to be removed. The water-leaving radiances of these near-IR channels over clear ocean waters are close to zero because of strong liquid water absorption above 0.8 μm. Through analysis of HICO imaging data containing features of shallow underwater objects, such as coral reefs, we have developed an empirical technique to correct for the second-order light effects in near-IR channels. HICO data acquired over Midway Island in the Pacific Ocean and the Bahamas Banks in the Atlantic Ocean are used to demonstrate the effectiveness of the new technique.

A new data-driven approach to modeling coastal bathymetry from hyperspectral imagery using manifold coordinates

Recently a new approach to modeling nonlinear structure in hyperspectral imagery was introduced [Bachmann et al., 2005]. The new method is a data-driven approach which extracts a set of coordinates that directly parameterize nonlinearities present in hyperspectral imagery, both on land and in the water column. The motivation for such a parameterization and its applicability to coastal bathymetry is based on the physical expectation that in shallow waters in a region that is homogeneous in bottom type and dissolved constituents, the reflectance at any particular wavelength should decay exponentially as a function of depth. If the rate varies with wavelength, then the reflectance should best be described by a nonlinear sheet or manifold in spectral space. Other changes in the structure of the data manifold can be expected as inherent optical properties (IOP) and bottom type vary. The manifold coordinates can be used to extract information concerning the latter as well. In the present work, we compare a manifold coordinate based approach to extracting bathymetry with prior work [Maness et al., 2005] based on radiative transfer modeling; the latter defined a set of look-up tables produced by repeated execution of a radiative transfer software package known as EcoLight. Comparative results for the two approaches are presented for the same Portable Hyperspectral Imager for low-light spectroscopy (PHILLS) airborne hyperspectral scene, acquired over the Indian River Lagoon in Florida in July 2004 and described in [Maness et al., 2005].