Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll a
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 sate...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2017-06-01
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| Series: | Frontiers in Marine Science |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/article/10.3389/fmars.2017.00190/full |
| _version_ | 1819157514218897408 |
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| author | Jordan Snyder Emmanuel Boss Ryan Weatherbee Andrew C. Thomas Damian Brady Carter Newell |
| author_facet | Jordan Snyder Emmanuel Boss Ryan Weatherbee Andrew C. Thomas Damian Brady Carter Newell |
| author_sort | Jordan Snyder |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-22T16:09:58Z |
| format | Article |
| id | doaj.art-c3ed49235ac444b291a16bf3ac58dc07 |
| institution | Directory Open Access Journal |
| issn | 2296-7745 |
| language | English |
| last_indexed | 2024-12-22T16:09:58Z |
| publishDate | 2017-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Marine Science |
| spelling | doaj.art-c3ed49235ac444b291a16bf3ac58dc072022-12-21T18:20:31ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452017-06-01410.3389/fmars.2017.00190263366Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll aJordan Snyder0Emmanuel Boss1Ryan Weatherbee2Andrew C. Thomas3Damian Brady4Carter Newell5Marine In-situ Sound and Color Lab, School of Marine Sciences, University of MaineOrono, ME, United StatesMarine In-situ Sound and Color Lab, School of Marine Sciences, University of MaineOrono, ME, United StatesSatellite Oceanography Data Lab, School of Marine Sciences, University of MaineOrono, ME, United StatesSatellite Oceanography Data Lab, School of Marine Sciences, University of MaineOrono, ME, United StatesDarling Marine Center, School of Marine Sciences, University of MaineWalpole, ME, United StatesMaine Shellfish Research and DevelopmentDamariscotta, ME, United StatesRemote 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.http://journal.frontiersin.org/article/10.3389/fmars.2017.00190/fullremote sensingLandsat 8oyster aquacultureatmospheric correctionhabitat suitability indexsea surface temperature |
| spellingShingle | Jordan Snyder Emmanuel Boss Ryan Weatherbee Andrew C. Thomas Damian Brady Carter Newell Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll a Frontiers in Marine Science remote sensing Landsat 8 oyster aquaculture atmospheric correction habitat suitability index sea surface temperature |
| title | Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll a |
| title_full | Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll a |
| title_fullStr | Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll a |
| title_full_unstemmed | Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll a |
| title_short | Oyster Aquaculture Site Selection Using Landsat 8-Derived Sea Surface Temperature, Turbidity, and Chlorophyll a |
| title_sort | oyster aquaculture site selection using landsat 8 derived sea surface temperature turbidity and chlorophyll a |
| topic | remote sensing Landsat 8 oyster aquaculture atmospheric correction habitat suitability index sea surface temperature |
| url | http://journal.frontiersin.org/article/10.3389/fmars.2017.00190/full |
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