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.
Protocol development for science based mapping of submerged aquatic vegetation (SAV) requires
comprehensive ground truth data describing the full range of variability observed in the target. The Indian
River Lagoon, Florida, extends along 250 km of the east central Florida coast adjacent to the Atlantic Ocean.
The lagoon crosses the transition zone between the Caribbean and Carolinian zoogeographic provinces
making it highly diverse. For large scale mapping and management of SAV four common and three
uncommon species of seagrass (Tracheophyta) and three broad groups of macroalgae; red algae
(Rhodophyta), green algae (Chlorophyta), and brown algae (Phaeophyta) are recognized. Based on technical
and cost limitations we established twenty, 7-10 km long flight transects for collection of 1.2 m2 spatial
resolution hyperspectral imagery covering the length of the lagoon. Emphasis was placed on the area near
the Sebastian River and adjacent Sebastian Inlet. Twenty six 40 m long ground truth transects were
established in the lagoon using 1 m2 white panels to mark each transect end. Each transect target was located
in the field using high precision GPS. Transects were positioned to cover a range of depths, SAV densities,
mixed and monotypic species beds, water quality conditions and general sediment types. A 3 m wide by 30
m long grid was centered on each transect to avoid spectral influences of the white targets. Water depth,
species of seagrasses, estimates of vegetation cover percentage, estimates of epiphytic density, and measured
canopy height were made for each 1 m2 (n=90). This target based grid arrangement allows for identification
and extraction of pixel based hyperspectral signatures corresponding to individual ground truth grid cells
without significant concern for rectification and registration error.
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.
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.
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.
Conference Committee Involvement (12)
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2023
4 September 2023 | Amsterdam, Netherlands
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2022
6 September 2022 | Berlin, Germany
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2021
13 September 2021 | Online Only, Spain
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2020
22 September 2020 | Online Only, United Kingdom
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2019
9 September 2019 | Strasbourg, France
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2018
10 September 2018 | Berlin, Germany
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2017
11 September 2017 | Warsaw, Poland
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2016
26 September 2016 | Edinburgh, United Kingdom
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015
23 September 2015 | Toulouse, France
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2014
24 September 2014 | Amsterdam, Netherlands
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2013
24 September 2013 | Dresden, Germany
Remote Sensing of the Ocean, Sea Ice, and Large Water Regions 2008
15 September 2008 | Cardiff, Wales, United Kingdom
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