Date of Award

Summer 8-18-2017

Level of Access

Open-Access Thesis

Degree Name

Master of Science (MS)

Department

Oceanography

Advisor

Emmanuel Boss

Second Committee Member

Damian Brady

Third Committee Member

Andrew C. Thomas

Abstract

Remote sensing data is useful for selection of aquaculture sites because it can provide water-quality products mapped with no cost to users. However, the spatial resolution of most ocean color satellites is too coarse to provide usable data within many estuaries. The more recently launched Landsat 8 satellite has both the spatial resolution and the necessary signal to noise ratio to provide temperature, as well as ocean color derived products along complex coastlines. The state of Maine (USA) has an abundance of estuarine indentations (~3,500 miles of tidal shoreline within 220 miles of coast), and an expanding aquaculture industry, which makes it a prime case-study for using Landsat 8 data to provide products suitable for aquaculture site selection. We collected the Landsat 8 scenes over coastal Maine, flagged clouds, atmospherically corrected the top-of-the-atmosphere radiances, and derived time varying fields (repeat time of Landsat 8 is 16 days) of temperature (100 m resolution), turbidity (30 m resolution), and chlorophyll-a (30 m resolution). We validated the remote-sensing-based products at several in situ locations along the Maine coast where monitoring buoys and programs are in place. Initial analysis of the validated fields revealed promising areas for oyster aquaculture. The approach used and the data collected to date show potential for other applications in marine coastal environments, including water quality monitoring and ecosystem management.

Included in

Oceanography Commons

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