projects > monitoring sub-aquatic vegetation through remote sensing > work plan
U.S. Geological Survey Greater Everglades Science Initiative (Place-Based Studies)
Fiscal Year 2004 Project Work Plan
A. GENERAL INFORMATION:
Project Title: Monitoring Sub-Aquatic Vegetation through Remote Sensing: A pilot study in Florida Bay
Seagrass beds are essential components of any marine ecosystem because they provide feeding grounds, nurseries, and habitats for many forms of marine life, including commercially valuable species; they are important foraging grounds for migratory birds; and they anchor sediments and impede resuspension and coastal erosion during storms. This valuable natural resource has been suffering die-offs around the world in recent years, yet the causes of these die-offs are undetermined. The purpose of this project is to use a number of tools - geographic, geologic, and biologic - to investigate the cause of seagrass die-off and to develop a tool that can be used to monitor the health of seagrass meadows. If we understand the causes of die-off and can easily monitor the health of seagrass beds, then resource managers have a tool for forecasting areas of potential die-offs. This pilot study will focus on Florida Bay, a region that suffered the loss of 40,000 ha of turtle grass in a die-off event that began in 1987, and a small, localized die-off in 1999. These events were well documented and provide a baseline for testing methods of monitoring grass beds remotely. Historical aerial photos, remotely sensed data, and data extracted from sediment cores will be used to examine the long-term sequences of events leading up to seagrass die-off events. An understanding of the sequence of events that precede die-offs is critical for resource managers, so further losses can be effectively prevented, and damaged systems can be restored.
Project Objectives and Strategy:
The objectives of this pilot study are to develop a methodology for monitoring spatial and temporal changes in sub-aquatic vegetation using remote sensing, satellite imagery, and aerial photography, and to analyze potential causes of seagrass die-off using geographic, geologic and biologic tools. The ultimate goal is to develop a method for forecasting potential sea-grass die-offs and to determine if remediation efforts would be cost-effective.
Florida Bay is selected for the pilot study because the thorough documentation of the 1987-1988 die-off event provides a baseline for examining data preceding and succeeding the event. In addition, a small well-studied die-off occurred in 1999-2000 at Barnes Key in Florida Bay. A 10-15 km2 portion of Florida Bay that encompasses areas affected by the 1987 and 1999 die-offs will be analyzed for this pilot study. Current remotely sensed data, aerial photos and satellite images from this area will be used to test different platforms, determine detection limits, and to attempt to isolate distinct signals for different types of vegetation. When ground-truthing is completed, archived remotely sensed data and/or aerial photographs can then be used to examine the sequences of events leading up to the die-offs. The remotely sensed data can be compared and compiled with the data collected by seagrass biologists in 1987 and 1999, and to sediment core data collected at the sites of seagrass die-off. Sediment cores provide a long-term perspective on changes in nutrient geochemistry, substrate, water chemistry (salinity, temperature, oxygen), and changes in the biota. The geologic, biologic and remotely sensed data will be integrated and analyzed to determine the patterns of change and sequences of events that occur in healthy seagrass beds and in beds undergoing a die-off.
Several remote sensor types will be compared in this study to determine the ideal sensor bands and spatial resolution necessary to detect and monitor the health of seagrass beds. The sensors to be tested include Landsat 7 (30m multi-spectral spatial resolution), ASTER (15 and 30m multi-spectral), Quickbird (2.5m multi-spectral and <1m panchromatic), and large-scale aerial photography (anticipated spatial resolution .25m with visible and near-infrared bands). Imagery with bands in the blue wavelength may help to penetrate water and infrared or near-infrared bands are predicted to perform better for resolving vegetation. It is theorized that through a combination of blue, and infrared bands and higher spatial resolution it will be possible to map the extent of seagrass beds. Although Landsat ETM+ 7 has several bands in desirable wavelengths, this sensor is predicted to be too course of a dataset to resolve individual seagrass beds. Landsat ETM+ may be used to develop an index of chlorophyll values that may be translated into a measure of seagrass health. ASTER's multiple infrared bands and increased spatial resolution may be successful in distinguishing between the types of vegetation, but these bands are not designed for water penetration. Higher spatial resolution platforms are predicted to have better mapping capabilities. The Quickbird sensor can provide 2.5m spatial resolution with multi-spectral capability. The multi-spectral bands include a blue band for water penetration and a near-infrared band for vegetation detection. Finally, aerial photography flown at low altitude represents the highest spatial resolution (.25m) and can be collected in visible and near-infrared to allow processing of blue and infrared bands. A combination of sensor types to maximize both spatial resolution and spectral signatures may provide the best solution for mapping and monitoring seagrass beds.
Potential Impacts and Major Products:
By integrating remotely sensed data, biological data and core data we can examine the long-term (decadal-scale) sequences of events leading up to die-off events. These data can be contrasted to normal seasonal changes that occur in healthy grass beds to establish criteria for identifying areas that may be on the threshold of experiencing a decline. This provides a very powerful predictive tool for resource managers. By examining the causes of die-off and the natural patterns of change in seagrass meadows over biologically significant periods of time we can determine the components of change that may be related to anthropogenic activities versus natural cycles of change. This information would allow resource managers to make informed decisions about the cost-effectiveness of and mechanisms for remediation, if an area of decline was identified via the predictive tool. Once the predictive tools and potential remediation tools have been developed in this pilot study, in well-studied seagrass meadows, the tools can be applied to threatened coastal ecosystems around the country and worldwide.
Primary products will include be GIS map product compiling all the data from the project for the study area, a journal article compiling the results from the tasks, and a general interest publication for resource managers and the public explaining the methodology and findings. Successful development of a repeatable methodology for mapping the location and health of seagrass beds and an increased understanding of the long-term factors affecting seagrass health will be the anticipated products of the research.
DOI, USGS, St. Petersburg, John Brock (Experimental Airborne Advanced Research Lidar - EAARL)
Florida, Florida Marine Research Institute, Paul Carlson and Barbara Blakesley (seagrass)
Florida, Florida Marine Research Institute, William Sargent (archive of Florida Bay aerial photos)
Florida, Florida International University, James Fourqurean (seagrass biologist)
Florida, State Agencies, Florida Department of Environmental Protection, Keys Marine Laboratory; field station: Contact: Lisa Tipsword
Virginia, University of Virginia, Jay Zieman (seagrass biologist)
Virginia, George Mason University, Department of Biology, Theodore Bradley (Botanist)
Department of Interior, National Park Service, Everglades National Park, Contact: Tom Armentano
Department of Commerce, National Oceanic and Atmospheric Administration, Florida Keys National Marine Sanctuary: Contact: William Causey
Department of Interior, U.S. Fish and Wildlife Service: Contact: Heather McSharry
Department of Interior, National Park Service, Biscayne National Park: Contact: Richard Curry and Sarah Bellmund
Department of Defense, U.S. Army, U.S. Army Corps of Engineers, Jacksonville District, South Atlantic Division: Contact: Debbie Peterson
Florida, State Agencies, South Florida Water Management District: Contacts: Rick Alleman and David Rudnick
Florida, Local Agencies, Dade County Environmental Resource Management (DERM): Contact: Gwen Burzycki
B. WORK PLAN
Title of Task 1: Evaluation of Remote Sensing Methods for Seagrass Detection
G. Lynn Wingard
Task Summary and Objectives:
The objective of this task is to select the best remote sensing platform and sensor type for monitoring the spatial extent and health of seagrasses in the study area. We will determine the ideal sensor bands and spatial resolution for detecting subaquatic vegetation using the different platforms and sensor types. The platforms and sensors to be tested include Landsat 7's Enhanced Thematic Mapper (ETM+) with 30m multi-spectral spatial resolution, TERRA's ASTER with 15 and 30m multi-spectral spatial resolution, Quickbird with 2.5m multi-spectral and <1m panchromatic spatial resolution, and large-scale natural color aerial photography. The study area is a 10-15 km2 portion of Florida Bay from Rabbit Key to Barnes Key that encompasses areas affected by the 1987 and 1999 die-offs will be analyzed for this pilot study (Figure1).
The subaquatic vegetation (SAV) in Florida Bay includes four species of true grasses and dozens of species of macrobenthic algae. Water depths range from near 0 on top of the shallow mud banks, where SAV can be emergent during low tides, to 3-4 meters in the basins and channels. The primary focus of the study is the seagrass Thalassia (Turtle Grass), which has suffered the extensive die-offs, and the effect that large mats of macro-benthic algae (primarily Chondria, Laurencia and Polysiphonia) may have on the health of Thalassia. We will investigate different methods for potentially discriminating types of SAV from remote sensing data. Imagery with bands in the blue and green wavelengths may help to penetrate water and infrared or near-infrared bands are predicted to perform better for resolving vegetation. Because water absorbs infrared energy with increasing depth, different band combinations must be evaluated to determine which one performs best at mapping both spatial extent and concentration or density of the seagrass beds. Bathymetric data for the study area will help to assess the accuracy of the sensor systems in water from less than a meter deep to several meters deep. Seagrass beds also range in size from several meters to hundreds of meters. It is theorized that through a combination of blue, and infrared bands and higher spatial resolution it will be possible to map the extent of seagrass beds. Although Landsat ETM+ 7 has several bands in desirable wavelengths, this sensor is predicted to be too course of a dataset to resolve small individual seagrass beds. Landsat ETM+ may be used to develop an index of chlorophyll values, which may be translated into a measure of seagrass health. ASTER's multiple infrared bands and increased spatial resolution may be successful in distinguishing between the types of vegetation, but these bands are not designed for water penetration. Higher spatial resolution platforms are predicted to have better mapping capabilities. The Quickbird sensor can provide 2.5m spatial resolution with visible and infrared capability. If Hyperion hyperspectral data is available at the time of this project, a test image may be acquired for comparison purposes. Finally, aerial photography flown at low altitude represents the highest spatial resolution and will be collected in natural color. A combination of sensor types to maximize both spatial resolution and spectral signatures may provide the best solution for mapping and monitoring seagrass.
Work to be undertaken during the proposal year and a description of the methods and procedures:
Data from the selected remote sensing systems will be acquired for a specific time period in FY04. Preferably, all imagery will be collected on the same date/time to ensure environmental variables are constant for all images and will be closely correlated with field mapping (task 2). If this is not possible, due to tasking and weather limitations, the best possible combination of imagery and image dates will be acquired. These data sets include Landsat 7 ETM+, ASTER, Quickbird, Natural color, 1:12,000 scale aerial photography, historical photography and, if available, a test image of Hyperion hyperspectral data.
Digital image processing will be performed on the Landsat, ASTER, and Quickbird imagery using spectral signature response ground truth data and several types of enhancements or processing techniques. Imagery data will be converted from radiance-at-sensor to reflectance prior to processing. Several band combinations from each sensor system may be used to maximize the effectiveness of the system for detecting seagrass habitats. The goal of the image processing is to develop the best possible band combination and processing technique for each sensor for the purpose of mapping seagrass habitat in Florida Bay. Once processed, image classes, which correspond to those used in the aerial photography interpretation step, will be developed for each sensor used. Ancillary information will be compiled for the study area that will include the bathymetry, tidal range, water temperature, and salinity. These data layers will assist in the processing of the satellite imagery and will also be used to help describe the results of the processing.
The aerial photography mapping protocol consists of stereoscopic photo interpretation, cartographic transfer, and digitization of seagrass habitat in accordance with previously used seagrass classification systems. Other important aspects of the protocol include the development of a classification system, validation with ground control data, quality control, and peer review. The information derived from the photography will subsequently be transferred using a Zoom Transfer Scope onto a stable medium overlaying USGS 1:12,000 scale quadrangle basemaps. Habitat classification done through the aerial photography interpretation will be stored as a geographic information system (GIS) data layer to be used for remote sensing correlation analysis. Historical photography will also be analyzed to evaluate spatial size and location related to historical die-off events. We will begin gathering these historical photographs in FY04, but interpretation will probably take place in FY05 once funding is secured.
The resultant image classifications of each sensor system will be correlated against both the independent ground truth data (task 2) and the aerial photography interpretation habitat classes for an assessment of accuracy. The different methodologies and image processing techniques will be evaluated based on their correlation with the habitat maps and ground truth data. The procedures will be documented and explained to show the comparison of sensor systems, band combinations, spatial resolution and correlation with ground truth.
Primary product generation will be geographically registered and geometrically corrected satellite and aerial photography of Barnes Key and Rabbit Key. From these sources GIS map layers will be developed showing locations and spectral signatures of seagrass beds. A remote sensing and aerial photography seagrass habitat map, bathymetric map, spectral profiles of seagrass habitat, GPS coordinates of seagrass site locations, and correlation tables for sensors will be developed. These map products will be used in field assessments and tested for accuracy. Successful development of a repeatable methodology for mapping the location and health of seagrass beds in Florida Bay will be the anticipated product of the research. This method will aid researchers in monitoring and analyzing environmental variables, which may affect seagrass health. Information and data will be presented to clients and colleagues at meetings and workshops, and will eventually be compiled for a journal article and a publication aimed at resource managers.
Title of Task 2: Field Mapping of Subaquatic Vegetation
Task Status (proposed or active): Proposed
Task Summary and Objectives:
The primary objective of this task is to provide the ground-truthing data for interpretation of the remote sensing data and aerial photographs. Ground truth data collection will be performed to coincide as closely as possible with imagery collection. Ground truth data consists of date/time, water temperature, water depth, tidal fluctuations, type of subaquatic vegetation, size and density of seagrass beds and substrate for individual seagrass beds within the study area. Turbidity and chlorophyll levels in the water will be measured. Ground control data will include spectral signatures of seagrass habitats acquired through a portable spectrometer. All ground truth data will be linked to geographic reference coordinates developed from global positioning systems (GPS) receivers. The secondary objective of this task is to collect information on seasonal changes in SAV and responses to environmental variables, such as salinity, water temperature, nutrients, etc. These data will provide the background information for interpreting the changes seen in the historical data (remote sensing, aerial photographs, and core data) by providing insights into the causes of changes in SAV distribution.
Work to be undertaken during the proposal year and a description of the methods and procedures:
Field mapping in the study area will commence in FY04. Three to six test sites (at scales ranging from 1m up to a maximum of 90 m2) will be selected within the study area that represent different environments, habitats and water depths typical of the area. These sites will be selected based on preliminary field observations and examinations of historical and current aerial photographs.
Investigations at each test site will include the following work. 1) All submerged aquatic vegetation (SAV) within the test areas will be mapped using GPS units. The perimeter of the grass beds and any associated barren sections will be measured and documented. Over the course of this project these boundaries will serve as a baseline to determine any expansion or contraction of vegetation that may occur. 2) The SAV within the test area will be identified to species level and a permanent reference collection of samples established. After the initial identification and sampling process is complete, the plant biomass density will be measured and documented by using a grid system and counting plant stems and/ or shoots within a random sampling of the grid layout. 3) Portable spectrometer readings will be made over areas of different types of SAV to determine the spectral signatures associated with each type. These data will be critical in interpreting the remote sensing data. 4) Water quality measurements will be taken including; salinity, temperature, turbidity, chlorophyll content, PH, dissolved oxygen, ammonia, nitrates, nitrites, etc. at each test site. 5) Water depth, sediment depth, and substrate type will be documented at each measured site. 6) Selected test sites will be monitored on a regular basis (4-8 week intervals) in order to establish seasonal variability within the submerged plant communities. The increases and decreases in abundance of various groups of SAV and the phytoplankton densities within the water column can then be established.
This task is part of James Murray's graduate student thesis at George Mason University (Dr. Ted Bradley, Advisor); data and results will be presented in talks and posters prepared for scientific meetings and workshops. A seasonal SAV species list will be developed and made available on the Ecosystem History of Florida Bay web site (Wingard) (http://sofia.usgs.gov/flaecohist/). Collections that are created will be archived and become part of the George Mason University Herbarium collection, which currently houses more than fifty thousand specimens and is used by the USGS, the Smithsonian Institution and many other universities. Results from this task will be compiled and incorporated with data from tasks 1 & 2 to prepare a journal article, posters, and general interest publications, some of which will be aimed at resource managers.
Title of Task 3: Historical perspective on the causes of seagrass die-off from sediment cores
Task Summary and Objectives:
The objective of this task is to examine the relationship between seagrass and environmental factors over a time-scale of years and decades by using sediment cores from two known and well-documented areas of seagrass die-off, Barnes Key and Rabbit Key. These cores preserve a record of the substrate, salinity, nutrient supply, and the fauna and flora present at a site. By examining the link between environmental factors and seagrass over an extended period, we can test hypotheses about the causes of seagrass die-off. These hypotheses include 1) changes in salinity; 2) changes in light availability; 3) changes in water temperature; 4) nutrient availability; 5) disease; and 6) increases in atmospheric dust (aerosols). These data will be compiled with the analysis of historical aerial photos and remotely sensed data (task 1) to determine 1) if any distinctive patterns in the sequence of events can be detected in the cores, the aerial photos, and or the remotely sensed data, and 2) in hindsight, did the aerial photographs and/or remotely sensed data pick up some signal to the beginning of the stressors that could be used as a predictive tool to monitor seagrass beds for future problems.
Work to be undertaken during the proposal year and a description of the methods and procedures:
In FY04 we will analyze a core collected in June 2001 from Barnes Key and process a core from Rabbit Key. Sampling and analyses of cores will follow methods established by the Florida Bay Ecosystem History Project (Brewster-Wingard, USGS, GD; Orem, USGS, GD). Cores will be dated using 210-Pb geochronology (Holmes, USGS, GD). Faunal and floral assemblage analyses will be conducted on 2-cm segments of the cores from Barnes and Rabbit Key; these data will be interpreted using a large dataset on the biology and ecology of modern Florida Bay fauna and flora (Wingard, Ecosystem History of Florida Bay Project; http://sofia.usgs.gov/flaecohist/). The presence of seagrass-indicator species (primarily molluscs in FY04) will be quantified in down-core samples. In FY05 additional analyses can be done including 1) downcore geochemical analyses to evaluate past changes in nutrients (C,N,P,S); 2) the occurrence of lignin phenols (seagrass biomarkers); 3) shell geochemistry (salinity and temperature); 4) stable isotopes (salinity and sources of water); and 5) atmospheric dust (aerosols). The analyses of the indicator-species and the shell geochemistry work will be an extension of ongoing and completed ecosystem history work in Florida Bay that has focused on historical salinity patterns (Brewster-Wingard and others).
Data from cores will be compiled, analyzed, and presented as a poster or talk at conferences and meetings with clients. Additionally, all data will be made available on line at http://sofia.usgs.gov/flaecohist/. An Open File Report will be produced on the cores and distributed to clients and cooperators. When the core analyses have been completed and the data compared and compiled with the historical aerial photograph analyses and remote sensing (task 1), a journal article for a scientific publication will be produced.
C. BRIEF DESCRIPTION ON HOW PROJECT TASKS SUPPORT THE DOI AND USGS EVERGLADES RESTORATION SCIENCE PLANS
The large scale die-off of seagrass in Florida Bay in 1987-88 was one of the primary factors stimulating a move towards restoration of more natural freshwater flows into Florida Bay. A major question persists - are changes in freshwater flow a factor in seagrass die-offs. This research attempts to address that question and as a result will provide information relevant to all three restoration goals listed by the task force - to get the water right, to restore preserve and protect natural habitats and species, and to foster compatibility between the built and natural systems. This project also addresses several USGS restoration science objectives: SO1, understanding ecosystem structure and function; SO2, determining the historical ecosystem setting; SO3, establishing baselines and targets; and SO5, predicting ecosystem response to change. By examining the causes of die-off and the natural patterns of change in seagrass meadows over biologically significant periods of time we can determine the components of change that may be related to anthropogenic activities versus natural cycles of change. This information would allow resource managers to make informed decisions about the cost-effectiveness of and mechanisms for remediation.
U.S. Department of the Interior, U.S. Geological Survey
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Last updated: 04 September, 2013 @ 02:08 PM(KP)