UROP Project
Video Analyses, Substrate, Deep-Sea Corals

Research Mentor: Dr Amy Baco-Taylor,
Department, College, Affiliation: EOAS, Arts and Sciences
Contact Email: abacotaylor@fsu.edu
Research Assistant Supervisor (if different from mentor): Virginia Biede
Research Assistant Supervisor Email: vbiede@fsu.edu
Faculty Collaborators: Sierra Landreth
Faculty Collaborators Email: sll22d@fsu.edu
Department, College, Affiliation: EOAS, Arts and Sciences
Contact Email: abacotaylor@fsu.edu
Research Assistant Supervisor (if different from mentor): Virginia Biede
Research Assistant Supervisor Email: vbiede@fsu.edu
Faculty Collaborators: Sierra Landreth
Faculty Collaborators Email: sll22d@fsu.edu
Looking for Research Assistants: No
Number of Research Assistants: 4
Relevant Majors: Environmental Science, Biology, Geology, Computer Science
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: In-person
Approximate Weekly Hours: 10,
Roundtable Times and Zoom Link: Not participating in the Roundtable
Number of Research Assistants: 4
Relevant Majors: Environmental Science, Biology, Geology, Computer Science
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: In-person
Approximate Weekly Hours: 10,
Roundtable Times and Zoom Link: Not participating in the Roundtable
Project Description
The goal of this project is to review deep-sea remotely operated vehicle videos to help characterize substrate on seamounts of the Hawaiian Ridge and Emperor Seamount Chain in the North Pacific. Students with appropriate backgrounds may develop an automated image analysis project. There is potential for this project to develop into characterization of habitats and comparisons among sites.Research Tasks: Video annotation, Data Entry, Data Management
Skills that research assistant(s) may need: Strong excel skills are required
Image J, coral point count, or BIIGLE software experience not required but would be helpful
R or GIS software experience helpful but not required
Experience with automated image analyses would be ideal but not required