Charles R. Bostater

Hyperspectral remote sensing protocol development for submerged aquatic vegetation in shallow waters

Submerged aquatic vegetation (SAV) is an important indicator of freshwater and marine water quality in almost all shallow water aquatic environments. Throughout the world the diversity of submerged aquatic vegetation appears to be in decline, although sufficient historical data, of sufficient quantitative quality is lacking. Hyperspectral remote sensing technology, available from low altitude aircraft sensors, may provide a basis to improve upon existing photographic regional assessments and monitoring concerned with the aerial extent and coverage of SAV. In addition, modern low altitude remote sensing may also help in the development of environmental satellite requirements for future satellite payloads. This paper documents several important spectral reflectance signature features which may be useful in developing a protocol for remote sensing of SAV, and which is transferable to other shallow water aquatic habitats around the world. Specifically, we show that the shape or curvature of the spectral reflectance absorption feature centered near the chlorophyll absorption region of ~ 675 nm is strongly influenced not only by the relative backscatter region between 530-560 nm, but by a “submerged vegetation red edge” that appears in the 695 to 700 nm region in extremely high density vegetative areas in very shallow waters (= 0.5m depth). This “aquatic biomass red edge” is also observable in deeper waters where there is a shallow subsurface algal boom as demonstrated in this paper. Use of this submerged aquatic red edge feature will become an important component of SAV remote sensing in shallow aquatic habitats, as well as in phytoplankton-related water quality remote sensing applications of surface phytoplankton blooms.

Synthetic Image Generation of Shallow Waters Using a Parallelized Hyperspectral Monte Carlo & Analytical Radiative Transfer Model

Modeled hyperspectral reflectance signatures just above the water surface are obtained from radiative transfer models to create synthetic images of the water surface. Images are displayed as 24 bit RGB images of the water surface using selected channel. Comparisons are made in this paper between a hyperspectral Monte Carlo and a hyperspectral layered analytical model of radiative transport applicable to shallow water types. Images at the selected wavelengths or channels centered at 490, 530 and 680 nm suggest the two models provide the same results when displayed as RGB images. The most sensitive parameters for generating realistic images are water depth and bottom reflectance in clean natural, optically shallow waters. The images clearly demonstrate the need importance of detailed and accurate water depths.

A grid enabled Monte Carlo hyperspectral synthetic image remote sensing model (GRID-MCHSIM) for coastal water quality algorithm

Previous studies indicate that parallel computing for hyperspectral remote sensing image generation is feasible. However, due to the limitation of computing ability within single cluster, one can only generate three bands and a 1000*1000 pixels image in a reasonable time. In this paper, we discuss the capability of using Grid computing where the so-called eScience or cyberinfrastructure is utilized to integrate distributed computing resources to act as a single virtual computer with huge computational abilities and storage spaces. The technique demonstrated in this paper demonstrates the feasibility of a Grid-Enabled Monte Carlo Hyperspectral Synthetic Image Remote Sensing Model (GRID-MCHSIM) for coastal water quality algorithm.

Temporal measurement and analysis of high-resolution spectral signatures of plants and relationships to biophysical characteristics

Measurements of temporal reflectance signatures as a function of growing season for sand live oak (Quercus geminata), myrtle oak (Q. myrtifolia, and saw palmetto (Serenoa repens) were collected during a two year study period. Canopy level spectral reflectance signatures, as a function of 252 channels between 368 and 1115 nm, were collected using near nadir viewing geometry and a consistent sun illumination angle. Leaf level reflectance measurements were made in the laboratory using a halogen light source and an environmental optics chamber with a barium sulfate reflectance coating. Spectral measurements were related to several biophysical measurements utilizing optimal passive ambient correlation spectroscopy (OPACS) technique. Biophysical parameters included percent moisture, water potential (MPa), total chlorophyll, and total Kjeldahl nitrogen. Quantitative data processing techniques were used to determine optimal bands based on the utilization of a second order derivative or inflection estimator. An optical cleanup procedure was then employed that computes the double inflection ratio (DIR) spectra for all possible three band combinations normalized to the previously computed optimal bands. These results demonstrate a unique approach to the analysis of high spectral resolution reflectance signatures for estimation of several biophysical measures of plants at the leaf and canopy level from optimally selected bands or bandwidths.

Methodology evaluation for remotely estimating water quality parameters in estuarine waters

Water absorption signatures were measured from water samples placed in a 50 cm pathlength cylindrical cuvette. Quantitative analysis of chlorophyll-a and dissolved organic matter (DOM- humic acid, fulvic acid, or tannic acid) was conducted using second derivative spectra followed by computation of double inflection ratio (DIR) spectra for all possible combinations of bands (from 362 - 1115 nm with 252 channels). A specially designed instrument system is described which allows measurements of absorption of particulate and dissolved organic matter (chlorophyll-a and DOM) in a water sample. The ability of the system to allow measurement of absorption signatures and relating the data to observed or in-situ water reflectance signatures measured from a moving or in-situ platform is described. The methods demonstrate the value of high spectral resolution signatures to estimate concentrations of the water quality parameters and an analytical technique using optimal ambient correlation spectroscopy for selecting bands or channels for estimating concentrations directly from spectral absorption signatures.

Shallow water surface gravity wave imaging, spectra and their use in shallow water dredging operations

Imaging of shallow waters using high resolution video imagery is described. Common to mono, stereo and trinocular imaging approaches from ground and airborne platforms is the need to validate the surface water wave field measurements, particularly the amplitude and specular reflectance of water surface small gravity waves. A technique for calibration and validation of water surface gravity wave field energy spectra is described. Results demonstrate the value of video imagery where water level staff gauges with approximately with 0.5 cm wave height accuracy are easily sensed using high definition videography. Essentially, a staff gauge placed in shallow water constructed from PVC materials with custom colored line coding are imaged at 30 H or high frame rates, followed by frame by frame analyses in order to detect the water level measured at 0.5 cm height intervals. The image based time series allow the development of shallow water gravity wave energy spectra using standard FFT analysis procedures. Spectral models based upon peak frequency, for example, are then used in a two dimensional water surface wave simulation model that generates radiative transfer based hyperspectral images of the water surface wave field. The simulated and observed water surface wave patch fields are compared by extracting vertical or horizontal transects within observed and simulated imagery. The approach allows one to developed spectral energy model probability distributions at low cost. The novel noncontact video sensing and image analysis methodology used to calibrate and validate shallow water gravity wave models yield a means for ultimately calculating bottom boundary velocities under measured or simulated wave fields. These boundary layer velocities can cause migration and horizontal particle fluxes (g cm-2 s-1), resuspension, settling, and increased turbidity during dredging operations, but not necessarily due to waterway dredging operations and activities.

Use of ground penetrating radar for determination of water table depth and subsurface soil characteristics at Kennedy Space Center

Sustainable use and management of natural resources require strategic responses using non-destructive tools to provide spatial and temporal data for decision making. Experiments conducted at John F. Kennedy Space Center (KSC) demonstrate ground penetrating radar (GPR) can provide high-resolution images showing depth to water tables. GPR data at KSC were acquired using a MALÅ Rough Terrain 100 MHz Antenna. Data indicate strong correlation (R2=0.80) between measured water table depth (shallow monitoring wells and soil auger) and GPR estimated depth. The study demonstrated the use of GPR to detect Holocene and Pleistocene depositional environments such as Anastasia Formation that consists of admixtures of sand, shell and coquinoid limestone at a depth of 20-25 ft. This corresponds well with the relatively strong reflections from 7.5 to 13 m (125-215 ns) in GPR images. Interpretations derived from radar data coupled with other non-GPR data (wells data and soil auger data) will aid in the understanding of climate change impacts due to sea level rise on the scrub vegetation composition at KSC. Climate change is believed to have a potentially significant impact potential on near coastal ground water levels and associated water table depth. Understanding the impacts of ground water levels changes will, in turn, lead to improved conceptual conservation efforts and identifications of climate change adaptation concepts related to the recovery of the Florida scrub jay (Aphelocoma coerulescens) and other endangered or threatened species which are directly dependent on a healthy near coastal scrub habitat. Transfer of this inexpensive and non-destructive technology to other areas at KSC, Florida, and to other countries, may prove useful in the development of future conservation programs.

Hyperspectral Remote Sensing - Using Low Flying Aircraft and Small Vessels in Coastal Littoral Areas

Large field of view sensors as well as flight line tracks of hyperspectral reflectance signatures are useful for helping to help solve many land and water environmental management problems and issues. High spectral and spatial resolution sensing systems are useful for environmental monitoring and surveillance applications of land and water features, such as species discrimination, bottom top identification, and vegetative stress or vegetation dysfunction assessments1. In order to help provide information for environmental quality or environmental security issues, it is safe to say that there will never be one set of sensing systems to address all problems. Thus an optimal set of sensors and platforms need to be considered and then selected. The purpose of this paper is to describe a set of sensing systems that have been integrated and can be useful for land and water related assessments related to monitoring after an oil spill (specifically for weathered oil) and related recovery efforts. Recently collected selected imagery and data are presented from flights that utilize an aircraft with a suite of sensors and cameras. Platform integration, modifications and sensor mounting was achieved using designated engineering representatives (DER) analyses, and related FAA field approvals in order to satisfy safety needs and requirements.

Hyperspectral simulation and recovery of submerged targets in turbid waters

Modeled hyperspectral reflectance signatures just above the water surface are obtained from radiative transfer models to create synthetic images of targets below the water surface. Images are displayed as 24 bit RGB images of the water surface using selected channels. Example model outputs are presented in this paper for a hyperspectral Monte Carlo and a hyperspectral layered analytical iterative model of radiative transport within turbid shallow water types. Images at the selected wavelengths or channels centered at 490, 530 and 680 nm suggests the two models provide quite similar results when displayed as RGB images. The techniques are demonstrated to the problem of extracting synthetic targets from hyperspectral synthetic images in the presence of water surface wave, using spectral wave models. The most sensitive parameters for generating realistic images are water depth and bottom reflectance in clean natural and optically shallow waters. Also presented are platforms for use in ports, harbors, inlets and waterways developed and designed for current and future monitoring to insure sustainable safe shallow water environments.

Plant pigment types, distributions, and influences on shallow water submerged aquatic vegetation mapping

Development of robust protocols for use in mapping shallow water habitats using hyperspectral imagery requires knowledge of absorbing and scattering features present in the environment. These include, but are not limited to, water quality parameters, phytoplankton concentrations and species, submerged aquatic vegetation (SAV) species and densities, epiphytic growth on SAV, benthic microalgae and substrate reflectance characteristics. In the Indian River Lagoon, Fl. USA we conceptualize the system as having three possible basic layers, water column and SAV bed above the bottom. Each layer is occupied by plants with their associated light absorbing pigments that occur in varying proportions and concentrations. Phytoplankton communities are composed primarily of diatoms, dinoflagellates, and picoplanktonic cyanobacteria. SAV beds, including flowering plants and green, red, and brown macro-algae exist along density gradients ranging in coverage from 0-100%. SAV beds may be monotypic, or more typically, mixtures of the several species that may or may not be covered in epiphytes. Shallow water benthic substrates are colonized by periphyton communities that include diatoms, dinoflagellates, chlorophytes and cyanobacteria. Inflection spectra created form ASIA hyperspectral data display a combination of features related to water and select plant pigment absorption peaks.