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Seagrass Resource Assessment Using WorldView-2 Imagery in the Redfish Bay, Texas

1
Harte Research Institute for Gulf of Mexico Studies, Texas A&M University-Corpus Christi, 6300 Ocean Drive, Unit 5869, Corpus Christi, TX 78412, USA
2
Department of Computing Sciences, Texas A&M University-Corpus Christi, 6300 Ocean Drive, Unit 5824, Corpus Christi, TX 78412, USA
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2019, 7(4), 98; https://doi.org/10.3390/jmse7040098
Received: 25 March 2019 / Revised: 25 March 2019 / Accepted: 4 April 2019 / Published: 10 April 2019
(This article belongs to the Special Issue Application of Remote Sensing Methods to Monitor Coastal Zones)
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Abstract

Seagrass meadows play important roles as habitats for many marine organisms, traps for sediment, and buffers against wave actions. The objective of this paper is to map seagrass meadows in the Redfish Bay, Texas from WorldView-2 imagery. Seagrass meadows grow in shallow and clear water areas in the Redfish Bay. The WorldView-2 satellite can acquire multispectral imagery from the bay bottom with 2 m spatial resolution 8 multispectral bands and 0.46 m panchromatic imagery. The top of atmosphere radiance was transformed to the bottom reflectance through the atmospheric correction and the water column correction. The object based image analysis was used to identify seagrass meadows distributions in the Redfish Bay. This investigation demonstrated that seagrass can be identified with 94% accuracy, although seagrass species cannot be satisfactorily recognized. The results implied that the WorldView-2 satellite imagery is a suitable data source for seagrass distribution mapping. View Full-Text
Keywords: coastal water; water depth correction; seagrass; object-based image analysis; WorldView-2 coastal water; water depth correction; seagrass; object-based image analysis; WorldView-2
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Su, L.; Huang, Y. Seagrass Resource Assessment Using WorldView-2 Imagery in the Redfish Bay, Texas. J. Mar. Sci. Eng. 2019, 7, 98.

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