Abstract
Mediterranean seagrasses have been hailed for their numerous ecosystem services, yet they are undergoing a decline in their coverage. The major complication with resolving this tendency is the sparsity of data on their overall distribution. This study addresses the suitability of the recently launched Sentinel-2 satellite for mapping the distribution of Mediterranean seagrass meadows. A comprehensive methodology is presented which applies atmospheric and analytical water column corrections and compares the performance of three different supervised classifiers. Remote sensing of the Thermaikos Gulf, northwestern Aegean Sea (Greece, eastern Mediterranean Sea) reveals that the utilization of Support Vector Machines on water column corrected reflectances yields best accuracies. Two Mediterranean seagrasses, Posidonia oceanica and Cymodocea nodosa, cover a total submerged area of 1.48km2 between depths of 1.4–16.5m. With its 10-m spatial resolution and 5-day revisit frequency, Sentinel-2 imagery can mitigate the Mediterranean seagrass distribution data gap and allow better management and conservation in the future in a retrospective, time- and cost-effective fashion.
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