Collaborative Development of Novel Remote Sensing Workflows for Assessing Oyster Reef Structural and Demographic Characteristics to Inform Management and Restoration - NERRS/NSC(NERRS Science Collaborative)
This project brought together oyster reef managers along the southeastern United States to evaluate the use of uncrewed aerial systems (UAS), or drones, as a novel tool for measuring changes in oyster reefs.
The Project
Oyster reefs in the southeastern United States offer an abundance of ecosystem services and support both recreational and commercial fisheries. To protect and enhance oyster reefs, resource managers in the southeastern United States need accurate and timely information to guide decisions on fishery closures and restoration efforts. Oyster resource managers and NERR staff in FL, GA, SC, and NC often rely on conventional monitoring approaches to inform management and restoration decisions, but these approaches have limitations. For example, methods like boat-based surveys and in situ quadrat sampling are time consuming and limited by spatial scale.
To overcome these limitations, this project evaluated the use of uncrewed aerial systems (UAS), or drones, as a novel tool for measuring reef structural and demographic characteristics relevant to reef function. Building on a previous collaborative initiative (NERRS Science Collaborative 2020 Catalyst), this project brought together oyster resource managers and restoration practitioners across four states. Together, the team developed and refined workflows for using drones to monitor key oyster reef metrics of interest across the region. The workflows provide standard procedures for data collection, analyzing drone imagery and generating estimates of:
reef height and elevation;
rugosity;
reef footprint and area;
shell substrate and oyster percent cover;
shell volumetric change; and,
oyster density and size structure.
These workflows have built technical capacity for the use of drones at the Reserves and state resource agencies. Application of the workflows has demonstrated that drones offer the capability to collect accurate, high resolution remote sensing data across entire reefs at a fraction of the cost of traditional sampling approaches. Integrating drones with existing oyster reef assessment efforts is allowing managers to map and model oyster reef ecosystem function and services on a scale that was previously unachievable.
Complete Metadata
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| description | This project brought together oyster reef managers along the southeastern United States to evaluate the use of uncrewed aerial systems (UAS), or drones, as a novel tool for measuring changes in oyster reefs. The Project Oyster reefs in the southeastern United States offer an abundance of ecosystem services and support both recreational and commercial fisheries. To protect and enhance oyster reefs, resource managers in the southeastern United States need accurate and timely information to guide decisions on fishery closures and restoration efforts. Oyster resource managers and NERR staff in FL, GA, SC, and NC often rely on conventional monitoring approaches to inform management and restoration decisions, but these approaches have limitations. For example, methods like boat-based surveys and in situ quadrat sampling are time consuming and limited by spatial scale. To overcome these limitations, this project evaluated the use of uncrewed aerial systems (UAS), or drones, as a novel tool for measuring reef structural and demographic characteristics relevant to reef function. Building on a previous collaborative initiative (NERRS Science Collaborative 2020 Catalyst), this project brought together oyster resource managers and restoration practitioners across four states. Together, the team developed and refined workflows for using drones to monitor key oyster reef metrics of interest across the region. The workflows provide standard procedures for data collection, analyzing drone imagery and generating estimates of: reef height and elevation; rugosity; reef footprint and area; shell substrate and oyster percent cover; shell volumetric change; and, oyster density and size structure. These workflows have built technical capacity for the use of drones at the Reserves and state resource agencies. Application of the workflows has demonstrated that drones offer the capability to collect accurate, high resolution remote sensing data across entire reefs at a fraction of the cost of traditional sampling approaches. Integrating drones with existing oyster reef assessment efforts is allowing managers to map and model oyster reef ecosystem function and services on a scale that was previously unachievable. |
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| identifier | gov.noaa.nmfs.inport:78650 |
| issued | 2024-09-01T00:00:00.000+00:00 |
| keyword |
[
"EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > REEF > OYSTER REEF",
"ACE Basin, SC NERR",
"Crassostrea virginica",
"UAS",
"drones",
"image analysis",
"monitoring",
"oyster demographics",
"oyster density",
"oyster percent cover",
"oyster reef",
"reef condition",
"reef demographics",
"reef elevation",
"reef footprint",
"reef rugosity",
"reef structure",
"remote sensing",
"shell volume",
"uncrewed aerial systems",
"Guana Tolomato Matanzas, FL NERR",
"North Carolina, NC NERR",
"North Inlet-Winyah Bay, SC NERR",
"Sapelo Island, GA NERR",
"DOC/NOAA/NOS/OCM > Office of Coastal Management, National Ocean Service, NOAA, U.S. Department of Commerce",
"NERRS"
]
|
| landingPage | https://www.fisheries.noaa.gov/inport/item/78650 |
| language |
[]
|
| license | https://creativecommons.org/publicdomain/zero/1.0/ |
| modified | 2024-09-01T00:00:00.000+00:00 |
| publisher |
{
"name": "Office for Coastal Management",
"@type": "org:Organization"
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|
| references |
[
"https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocm/dmp/pdf/78650.pdf"
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|
| rights | otherRestrictions, unclassified |
| spatial | -79.15,33.204,-79.285,33.375 |
| temporal | 2022-10-01T00:00:00+00:00/2024-09-01T00:00:00+00:00 |
| title | Collaborative Development of Novel Remote Sensing Workflows for Assessing Oyster Reef Structural and Demographic Characteristics to Inform Management and Restoration - NERRS/NSC(NERRS Science Collaborative) |
