Details:

Journal Title:
Frontiers in Marine Science
Personal Author:
Snyder, Jordan ; Boss, Emmanuel ; Weatherbee, Ryan ; Thomas, Andrew C. ; Brady, Damian ; ... More +
Snyder, Jordan ; Boss, Emmanuel ; Weatherbee, Ryan ; Thomas, Andrew C. ; Brady, Damian ; Newell, Carter Less -
NOAA Program & Office:
OAR (Oceanic and Atmospheric Research) ; Sea Grant
OAR (Oceanic and Atmospheric Research) ; Sea Grant Less -
Sea Grant Program:
MEU (Maine Sea Grant)
Description:
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.
Keywords:
[+]
Landsat Satellites
Oysters
Remote Sensing

Source:
Front. Mar. Sci. 4:190
DOI:
https://doi.org/10.3389/fmars.2017.00190
Sea Grant Document Number:
MEU-R-17-012
Document Type:
Journal Article
Rights Information:
CC BY
Compliance:
Library
Main Document Checksum:
[+]
urn:sha256:7330d3cc0c690e3d76bb81876926941191b0798bdfd555ec44404db680beda2e
File Type:

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