Geodatabase Development to Support Hyperspectral Imagery Exploitation

Geodatabase development for coastal studies conducted by the Naval Research Laboratory (NRL) is essential to support the exploitation of hyperspectral imagery (HSI). NRL has found that the remote sensing and mapping science community benefits from coastal classifications that group coastal types based on similar features. Selected features in project geodatabases relate to significant biological and physical forces that shape the coast. The project geodatabases help researchers understand factors that are necessary for imagery post processing, especially those features having a high degree of temporal and spatial variability. NRL project geodatabases include a hierarchy of environmental factors that extend from shallow water bottom types and beach composition to inland soil and vegetation characteristics. These geodatabases developed by NRL allow researchers to compare features among coast types. The project geodatabases may also be used to enhance littoral data archives that are sparse. This paper highlights geodatabase development for recent remote sensing experiments in barrier island, coral, and mangrove coast types

Very Shallow Water Bathymetry Retrieval from Hyperspectral Imagery at the Virginia Coast Reserve (VCR\u2707) Multi-Sensor Campaign

A number of institutions, including the Naval Research Laboratory (NRL), have developed look up tables for remote retrieval of bathymetry and in-water optical properties from hyperspectral imagery (HSI) [6]. For bathymetry retrieval, the lower limit is the very shallow water case (here defined as \u3c 2m), a depth zone which is not well resolved by many existing bathymetric LIDAR sensors, such as SHOALS [4]. The ability to rapidly model these shallow water depths from HSI directly has potential benefits for combined HSI/LIDAR systems such as the Compact Hydrographic Airborne Rapid Total Survey (CHARTS) [10]. In this study, we focused on the validation of a near infra-red feature, corresponding to a local minimum in absorption (and therefore a local peak in reflectance), which can be correlated directly to bathymetry with a high degree of confidence. Compared to other VNIR wavelengths, this particular near-IR feature corresponds to a peak in the correlation with depth in this very shallow water regime, and this is a spectral range where reflectance depends primarily on water depth (water absorption) and bottom type, with suspended constituents playing a secondary role

Linking goniometer measurements to hyperspectral and multi-sensor imagery for retrieval of beach properties and coastal characterization

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\u2711). Focus areas for VCR\u2711 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\u2711 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\u2711

A Field Portable Hyperspectral Goniometer for Coastal Characterization

During an airborne multi-sensor remote sensing experiment at the Virginia Coast Reserve (VCR) Long Term Ecological Research (LTER) site in June 2011 (VCR '11), first measurements were taken with the new NRL Goniometer for Outdoor Portable Hyperspectral Earth Reflectance (GOPHER). GOPHER measures the angular distribution of hyperspectral reflectance. GOPHER was constructed for NRL by Spectra Vista Corporation (SVC) and the University of Lethbridge through a capital equipment purchase in 2010. The GOPHER spectrometer is an SVC HR -1024, which measures hyperspectral reflectance over the range from 350 -2500 nm, the visible, near infrared, and short-wave infrared. During measurements, the spectrometer travels along a zenith quarter -arc track that can rotate in azimuth, allowing for measurement of the bi-directional reflectance distribution function (BRDF) over the whole hemisphere. The zenith arc has a radius of approximately 2m, and the spectrometer scan pattern can be programmed on the fly during calibration and validation efforts. The spectrometer and zenith arc assembly can be raised and lowered along a mast to allow for measurement of uneven terrain or vegetation canopies of moderate height. Hydraulics on the chassis allow for leveling of the instrument in the field. At just over 400 lbs, GOPHER is a field portable instrument and can be transformed into a compact trailer assembly for movement over long distances in the field

C. Reid Nichols

Col C. Reid Nichols USMCR (Ret) founded Marine Information Resources Corporation (MIRC) in 1998 to provide applied oceanographic services for operational organizations. He holds a 100-Ton USCG Masters License and Project Management Professional credentials. He plans and executes coastal and estuarine research, worldwide. He supports SURA as the Coastal and Environmental Research Program Manager. Current MIRC projects involve technical support to industry

C. Reid Nichols

Col C. Reid Nichols USMCR (Ret) founded Marine Information Resources Corporation (MIRC) in 1998 to provide applied oceanographic services for operational organizations. He holds a 100-Ton USCG Masters License and Project Management Professional credentials. He plans and executes coastal and estuarine research, worldwide. He supports SURA as the Coastal and Environmental Research Program Manager. Current MIRC projects involve technical support to industry

Session 1 Paper - Contemporary Expeditionary Warfare for Scientists and Engineers

Expeditionary forces from many countries have deployed to mitigate the effects of natural disasters and human conflicts. Approaches are usually linked to the nation’s maritime strategy. Expeditionary forces provide rapid response to man-made disruptions such as mass casualties by terrorists, vessel hijackings by pirates, murders by drug cartels, and nuclear accidents. Recent examples include Humanitarian Assistance/Disaster Response (HA/DR) and Non Combatant Evacuation Operations (NEO). HA/DR type missions have been planned and executed to mitigate the effects of catastrophic tropical cyclones, flooding, wild fires, and tsunami. NEO missions are focused on the evacuation of a nation’s citizens and other foreigners from threatened areas abroad. The need for robust capabilities in this area in both expeditionary warfare and disaster recovery are required so that governments can perform their civil functions. This type of crisis response requires expeditionary forces to be self-sustaining and make data-driven decisions in austere and chaotic environments. Technology solutions have been developed to identify, study and resolve expeditionary warfare and force protection challenges, especially along dynamic coasts that are modified by waves, tides, and shallow water processes. This paper will highlight the impact of waves, tides, and shallow water processes. There are many other environmental factors that are required to support expeditionary warfare

Coastal and Inland Aquatic Data Products for the Hyperspectral Infrared Imager (HyspIRI)

The HyspIRI Aquatic Studies Group (HASG) has developed a conceptual list of data products for the HyspIRI mission to support aquatic remote sensing of coastal and inland waters. These data products were based on mission capabilities, characteristics, and expected performance. The topic of coastal and inland water remote sensing is very broad. Thus, this report focuses on aquatic data products to keep the scope of this document manageable. The HyspIRI mission requirements already include the global production of surface reflectance and temperature. Atmospheric correction and surface temperature algorithms, which are critical to aquatic remote sensing, are covered in other mission documents. Hence, these algorithms and their products were not evaluated in this report. In addition, terrestrial products (e.g., land use land cover, dune vegetation, and beach replenishment) were not considered. It is recognized that coastal studies are inherently interdisciplinary across aquatic and terrestrial disciplines. However, products supporting the latter are expected to already be evaluated by other components of the mission. The coastal and inland water data products that were identified by the HASG, covered six major environmental and ecological areas for scientific research and applications: wetlands, shoreline processes, the water surface, the water column, bathymetry and benthic cover types. Accordingly, each candidate product was evaluated for feasibility based on the HyspIRI mission characteristics and whether it was unique and relevant to the HyspIRI science objectives

Hyperspectral benthic mapping from underwater robotic platforms

We live on a planet of vast oceans; 70% of the Earth's surface is covered in water. They are integral to supporting life, providing 99% of the inhabitable space on Earth. Our oceans and the habitats within them are under threat due to a variety of factors. To understand the impacts and possible solutions, the monitoring of marine habitats is critically important. Optical imaging as a method for monitoring can provide a vast array of information however imaging through water is complex. To compensate for the selective attenuation of light in water, this thesis presents a novel light propagation model and illustrates how it can improve optical imaging performance. An in-situ hyperspectral system is designed which comprised of two upward looking spectrometers at different positions in the water column. The downwelling light in the water column is continuously sampled by the system which allows for the generation of a dynamic water model. In addition to the two upward looking spectrometers the in-situ system contains an imaging module which can be used for imaging of the seafloor. It consists of a hyperspectral sensor and a trichromatic stereo camera. New calibration methods are presented for the spatial and spectral co-registration of the two optical sensors. The water model is used to create image data which is invariant to the changing optical properties of the water and changing environmental conditions. In this thesis the in-situ optical system is mounted onboard an Autonomous Underwater Vehicle. Data from the imaging module is also used to classify seafloor materials. The classified seafloor patches are integrated into a high resolution 3D benthic map of the surveyed site. Given the limited imaging resolution of the hyperspectral sensor used in this work, a new method is also presented that uses information from the co-registered colour images to inform a new spectral unmixing method to resolve subpixel materials

The Photometric Effect of Macroscopic Surface Roughness on Sediment Surfaces

The focus of this work was on explaining the effect of macroscopic surface roughness on the reflected light from a soil surface. These questions extend from deciding how to best describe roughness mathematically, to figuring out how to quantify its effect on the spectral reflectance from a soil’s surface. In this document, I provide a background of the fundamental literature in the fields of remote sensing and computer vision that have been instrumental in my research. I then outline the software and hardware tools that I have developed to quantify roughness. This includes a detailed outline of a custom LiDAR operating mode for the GRIT-T goniometer system that was developed and characterized over the course of this research, as well as proposed methods for using convergent images acquired by our goniometer system’s camera to derive useful structure from motion point clouds. These tools and concepts are then used in two experiments that aim to explain the relationship between soil surface roughness and spectral BRF phenomena. In the first experiment, clay sediment samples were gradually pulverized into a smooth powderized state and in steps of reduced surface roughness. Results show that variance in the continuum spectra as a function of viewing angle increased with the roughness of the sediment surface. This result suggests that inter-facet multiple scattering caused a variance in absorption band centering and depth due to an increased path length traveled through the medium. In the second experiment, we examine the performance of the Hapke photometric roughness correction for sand sediment surfaces of controlled sample density. We find that the correction factor potentially underpredicts the effect of shadowing in the forward scattering direction. The percentage difference between forward-modeled BRF measurements and empirically measured BRF measurements is constant across wavelength, suggesting that a factor can be empirically derived. Future results should also investigate the scale at which the photometric correction factor should be applied. Finally, I also outline a structure from motion processing chain aimed at deriving meaningful metrics of vegetation structure. Results show that correlations between these metrics and observed directional reflectance phenomena of chordgrass are strong for peak growing state plants. We observe good agreement between destructive LAI metrics and contact-based LAI metrics