We work across disciplines and with the Smithsonian MarineGeo program to map eelgrass beds while training community partners and citizen scientists about the use of UAV’s for mapping environmental change along the west coast of the U.S.
NSF & Smithsonian Eelgrass Drone Mapping
About NSF Project
A new collaborative $1.3 million dollar grant from the National Science Foundation (NSF) supports Citizen Science GIS at University of Central Florida (UCF). Dr. Timothy L. Hawthorne serves as PI and Dr. Bo Yang serves as lead post-doc researcher of the UCF portion of the grant. The collaborative grant includes faculty and students from a variety of universities and organizations, including MarineGeo at the Smithsonian Institution, Cornell University, University of California-Davis, San Diego State University, Oregon State University, University of Alaska Fairbanks, and Hakai Institute.
Mapping Eelgrass Meadow Extent and Dynamics with Drones
The UCF portion of the project uses Unmanned Aerial Systems (UAS), i.e. drones, to measure eelgrass meadow extent, patchiness, and dynamics through time. Drone imagery will be collected at least annually in coordination with in situ sampling which will also be used to validate the imagery by ground-truthing across a range of points within each meadow. Because eelgrass extent in some regions is subtidal and challenging to visualize from the air, we will utilize multi-spectral drone mapping technology and allocate 4-6 days at each site for each drone mission to maximize ideal conditions for collecting drone imagery, striving for lowest spring tides, and calm, bright conditions with roughly vertical sunlight. Multiple mapping strategies will be included in the project, including multi-spectral drone mapping, historical satellite imagery, in situ measurements with Ground Control Points (GCPs), atmosphere corrections, and GIS analyses.
In addition, Citizen Science GIS will lead the training of all community partners, as well as citizen scientists, in the use of drones for research at the six study regions. The team has strong experience with the challenges and sensitivities of working with drones in scientific research. A portion of Dr. Hawthorne’s current NSF REU Site examines the use of drones in community based research and also trains students and community partners in safe drone operations. The Citizen Science GIS team, which includes Federal Aviation Administration (FAA) Part 107 drone certified pilots, will lead all community partners in drone training sessions.
Citizen Science GIS team is internationally recognized for its community-based uses of GIS and drones. Engagement of amateur drone pilots through this project has the potential to greatly increase the spatial and temporal resolution of data used in measuring eelgrass ecosystem responses to climate change and disease. Hawthorne’s team will develop an Open Data Portal through ArcGIS Online for community partners to share their drone imagery, and to make GIS data and multimedia more accessible to the public. Specifically, we will develop a series of Esri Story Maps (combining location-based data, maps, drone imagery, and multimedia) to share the story of our work. All of these activities are especially timely as climate warming, other human impacts, and wasting disease appear to be growing threats to seagrasses worldwide and there is an urgent need for more and better quantitative data to establish baselines and time-series in service of effective management.
National Science Foundation Abstract
Click here if you’d like to read the National Science Foundation Abstract of Award for this project.
Drone Mapping sites
Click here for the Drone Mapping sites for west coast in summer 2019
Fieldwork for mapping eelgrass of west coast
If you have questions about the NSF eelgrass drone mapping project, please contact Dr. Timothy Hawthorne at University of Central Florida at firstname.lastname@example.org or Dr. Bo Yang at email@example.com.
Disclaimers: This project is funded by National Science Foundation
Division Of Ocean Sciences Program Award #1829890. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.