Eelgrass (Zostera marina L.) is a marine angiosperm plant that grows throughout coastal areas in Atlantic Canada. Eelgrass meadows provide numerous ecosystem services and while they have been acknowledged as important habitats, their location, extent and health in Atlantic Canada are poorly understood. Our study examines the effectiveness of WorldView-2 and Pléiades optical satellite imagery to map eelgrass presence in Tabusintac, New Brunswick, an estuarine lagoon with extensive eelgrass coverage. The imagery was classified using two supervised classifiers: the parametric Maximum Likelihood Classifier (MLC) and the non-parametric Random Forests (RF) classifier. While RF was expected to produce higher classification accuracies, it was shown not to be much better than MLC. The overall validation accuracy was 96.36% for both the RF and MLC classifiers when applied to the WorldView-2 8-band imagery. With MLC, WorldView-2 imagery outperformed Pléiades imagery. Limitations of the study are discussed, including the possible reasons for the low performance of the Pléiades classification.
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