Steven G. Ackleson, United States Naval Research Laboratory, United States
Frontiers in Marine Science
Frontiers in Marine Science
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Copyright © 2017 Snyder, Boss, Weatherbee, Thomas, Brady and Newell. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Remote sensing data is useful for selection of aquaculture sites because it can provide water-quality products mapped over large regions at low cost to users. However, the spatial resolution of most ocean color satellites is too coarse to provide usable data within many estuaries. The Landsat 8 satellite, launched February 11, 2013, 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 new areas for oyster aquaculture. The approach used is applicable to other coastal regions and the data collected to date show potential for other applications in marine coastal environments, including water quality monitoring and ecosystem management.
Snyder, Jordan; Boss, Emmanuel; Weatherbee, Ryan; Thomas, Andrew C.; Brady, Damian; and Newell, Carter, "Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll a" (2017). Miscellaneous Publications. 12.
Snyder J, Boss E, Weatherbee R, Thomas AC, Brady D and Newell C (2017) Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll a. Front. Mar. Sci. 4:190. doi: 10.3389/fmars.2017.00190
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