Florida
Environmental Research Institute is currently focusing on four major
projects,
dealing with sampling and forecasting the inherent optical properties
(IOPs) and apparent optical properties (AOPs) of the coastal ocean,
the cycling of colored dissolved organic matter (CDOM), and the atmospheric
correction of hypersectral remote sensing data. The following provides
a general overview of our objectives and what we hope to accomplish
as well as links to data collected, more current and specific information,
and collaborators.
- Hyperspectral Remote Sensing of the Coastal Ocean: Adaptive Sampling and Forecasting of Nearshore In Situ Optical Properties
- Hyperspectral Modeling of Harmful Algal Blooms on the West Florida Shelf
- Coupling Simulated Ocean Reflectance to the Atmospheric Correction of Hyperspectral Images
- The Ecological Cycling of Colored Dissolved Organic Matter
- Center for Integrative Coastal Observation, Research and Education (CI-CORE)
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Hyperspectral Remote Sensing of the Coastal Ocean: Adaptive Sampling and Forecasting of Nearshore In Situ Optical Properties |
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Experiment Information Coupled Physical/Bio-Optical Model Experiments at LEO-15
Objectives We propose to develop and validate an integrated adaptive sampling and modeling system for nowcasting and forecasting the 3-dimensional inherent optical properties (IOPs) off of the New Jersey coast. This will be accomplished by developing an integrated observation network that will provide real-time data to allow for adaptive sampling in near-shore coastal waters. These data will also be used to develop hyperspectral remote sensing techniques for optically complex coastal waters. In addition, it will be used to provide the physical, chemical, biological, and optical data necessary to develop coupled data assimilative hydrodynamic ecosystem models. This project is part of a larger Office of Naval Research ( ONR ) effort at the Rutgers University Long-term Ecosystem Observatory ( LEO-15 ) to collect, model, assimilate, and simulate high resolution 3-D physical, biological, chemical, and optical data. Our objectives are to collect, analyze, assimilate, and simulate hyperspectral inherent and apparent optical properties (IOPs and AOPs) at LEO-15. In particular, we wish to build upon an existing oceanic version of a predictive ecological simulation (EcoSim 1.0) to develop the tools, techniques, and code to transform this model into a data assimilative, prognostic coastal ocean model of IOPs and AOPs. Approach Working within a larger framework of experimentalists and physical numerical modelers, we are collecting and analyzing hyperspectral data, both in situ and from remote-sensing platforms, and modifying ecological code to develop the data assimilation techniques necessary for prognostic optical simulations. The data are collected as part of the Coastal Predictive Skill Experiments (CPSE) each summer at the LEO-15, offshore of Tuckerton, NJ. The CPSE represented a multi-institution effort funded by ONR through the Hyperspectral Coupled Ocean Dynamic Experiment ( HyCODE ), the Coastal Ocean Modeling and Observation Program (COMOP), and the two awards from the National Ocean Partnership Program (NOPP). Additional hyperspectral data have been collected as part of the ONR Coastal Benthic Optical Properties ( COBOP ) field experiment at Lee Stocking Island, Bahamas. Our participation in the COBOP experiment focused on data collection and inter-calibration of a new hyperspectral surface water buoy from Satlantic, Inc. (Satlantic H-TSRB), which is to be deployed at the LEO-15 site in July 2000. Impact/Applications Forecasting the near-shore optical properties requires the correct numerical formulation of the physical, chemical, biological, and optical interactions in the coastal ocean. Once this formulation is accomplished, forecasting requires the ability to assimilate remotely sensed data to constraint the solution to realistic projections. The instrumentation and techniques developed as part of this program are a necessary component of the forecasting process.
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Hyperspectral Modeling of Harmful Algal Blooms on the West Florida Shelf |
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FSLE July 2000 | FSLE November 2000 | FSLE April 2001 Introduction The occurrence of Harmful Algal Blooms (HABs) on the West Florida Shelf in 21 of the last 22 years has caused massive fish, invertebrate, and bird kills. In an attempt to discern the casual mechanisms for these HABs, NOAA/EPA/ONR established the Ecology and Oceanography of Harmful Algal Blooms ( ECOHAB ) program on the West Florida Shelf. ONR's participation in ECOHAB is part of a larger effort to simulate the inherent and apparent optical properties (IOPs and AOPs) using the West Florida shelf as an initial test case. Objectives Our objective is to couple a hyperspectral optical model that incorporates constituent specific optical properties to an ecological model of seven functional groups of competing microalgae. The resultant simulation is to be physically forced at different spatial scales and validated by moored, aircraft, and satellite optical data streams. This simulation will be used to test whether the spectral light harvesting abilities of G. breve (which includes pigment optimization and diurnal migration) provides a negative feedback on the total phytoplankton community, enhancing the competitive capabilities of G. breve for other necessary resources (i.e., nutrients). Approach Ecological modeling of phytoplankton is still in a state of infancy. Most attempts at simulating the microalgal content of the water column rely on reproducing the areal distribution of chlorophyll a . However, chlorophyll a does not adequately describe the total assemblage, or the individual components, of the phytoplankton community. Thus, the assumption of adequacy in reproducing fields of chlorophyll a with simplified numerical schemes fails to address the ecological interactions that are critical to HABs. Our approach is to simulate the dominant functional groups of the phytoplankton assemblage with their attendant sources and sinks. In this way, we hope to develop prognostic simulations of the optical, chemical, and biological responses to the physical forcing on the West Florida Shelf. Impact/Applications Reasonable formulation of the physical, chemical, biological, and optical interactions of the marine environmental into a numerical simulation should provide us with the best opportunity to forecast the probability of a red tide occurrence on the West Florida Shelf. In addition, a validated simulation would also provide estimates of the depth-distribution of IOPs and AOPs. We expect to derive a transportable version of EcoSim to apply to Naval regions of interest.
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Coupling Simulated Ocean Reflectance to the Atmospheric Correction of Hyperspectral Images |
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FSLE July 2000 | FSLE November 2000 | FSLE April 2001 HyCODE/LEO-15 Flight Information Objectives We propose to develop the hyperspectral remote sensing collection, processing, and analytical capabilities to test the hypothesis that simulated depth depending IOPs and water-leaving radiance can be used to refine the atmospheric correction algorithms in coastal waters for selected regions of a remotely sensed image. This will lead to the coupling of ecological simulations to atmospheric correction routines to provide a more accurate derivations of the in-water IOPs and AOPs in the coastal marine environment. In addition, we will investigate and develop a deployment plan for hyperspectral imaging systems on unmanned aircraft vehicles, focusing on high altitude, extended deployment vehicles. Approach Hyperspectral data will be collected at two ONR-funded study sites - the West Florida Shelf and the LEO-15 site off the New Jersey coast. We wish to focus data collection on Unmanned Aircraft Vehicle (UAV) deployment of the Ocean PHILLS. These data will be used to integrate numerical simulations of the marine environment into the atmospheric correction algorithms. Specifically, we will use the simulated output of water-leaving radiance from ground-truthed areas in aircraft and satellite images. The simulated water-leaving radiance will be used as bottom boundary conditions for atmospheric correction methods. This method will thus provide a greater number of (simulated) ground control points to correct any one image. Impact/Applications The study of oceanic remote sensing is based on the premise that knowledge of the surface water IOPs and AOPs will allow for the vertical description of the optical and biological characteristics of the water column. The closure between optical remote sensing data (aircraft or satellite), downwelling light, geometric structure of the underwater light field, water-leaving radiance and direction, and IOPs at specific sites is a necessary step in the usage of remote sensing data. The hope is that optical closure from a complete data set will eventually allow the development of algorithms that describe the optical, biological, and physical characteristics of the water column strictly from remote sensing data, e.g., inversion algorithms.
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Introduction The cycling of colored dissolved organic matter (CDOM) in the ocean has important biogeochemical and optical implications. The vast majority of organic carbon in the oceans resides as dissolved organic matter (DOM), and its biological and photochemical reactivity are two processes that are directly involved in its oceanic cycles. The biological and photochemical CDOM processes are determined by the physical, chemical, and biological interactions, i.e., the ecological interactions, of the marine environment. Objectives We wish to derive the fundamental principles of CDOM cycling. We propose to synthesize the available research into a set of prognostic ecological equations, which will be tested against, and validated by, an ongoing CDOM laboratory and field program. These CDOM ecological equations will then be incorporated into a larger Ecological Simulations (EcoSim 2.0), which seeks to predict the time dependent change in vertical inherent and apparent optical properties. Approach We hypothesize that CDOM cycling is a deterministic process, one that can be explained by physical, chemical, and biological interactions. Our approach is to couple experimental data with environmental modeling to lead to the development of a set of ecological equations that will resolve the sources and sinks of CDOM, and the impacts on water column IOPs and AOPs. Impact/Applications The impacts of the biogeochemical cycling of carbon, nitrogen, phosphorous, and iron through the dissolved organic pool are a critical issue in understanding global chemical cycling, and commensurate anthropogenic impacts. This is especially true of the coastal ocean where diffuse and point source run-off of nutrients and organic matter yield dramatic changes in the near-shore environment. Understanding the photochemical and biological changes of the CDOM pool is paramount to understanding the biogeochemical relevance of DOM cycling. Additionally, this research has direct impacts on the prediction of IOPs and AOPs. The absorption of light at the blue end of the spectrum can be dominated by CDOM. The strength of the CDOM signal can rapidly change by over an order of magnitude as one moves from coastal to oceanic waters. The impacts of CDOM on water clarity can thus be quite dramatic.
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Center for Integrative Coastal Observation, Research and Education (CI-CORE) |
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Managing the commercial, recreational and environmental burdens placed on California's coastal resources by agriculture, industry and urban development requires better understanding of coastal ocean dynamics. To this end, the California State University (CSU) has established CI-CORE. Leveraging the expertise of CSU institutional partners, the CI-CORE observatory will be distributed along the entire 1200 miles of California coastline. This distribution uniquely positions CI-CORE to address the variety of challenges to coastal environmental quality, including watershed alteration, shoreline erosion, chemical contamination of food webs, depletion of fish stocks, toxic plankton blooms, marine-borne pathogens, and the rapid invasion of coastal and estuarine waters by non-indigenous species.
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