Precise classification of coastal benthic habitats using high resolution Worldview-2 imagery

Abstract

The analysis of the seafloor in shallow waters using remote sensing imagery at very high spatial resolution is a very challenging topic due to the minimum signal level received; the presence of noisy contributions from the atmosphere, solar reflection, foam, turbidity and water column; and the limited spectral information available for the classification at such depths that impedes, for example, the extraction of vegetation indices. In this complex scenario we have developed a mapping methodology that involves the precise application of pre-processing techniques and the use of efficient classification algorithms. In particular, after a detailed assessment, support vector machines achieved the best performance using the appropriate kernel and parameters. Two natural areas located at the Canary Islands (Spain) have been selected for their benthic habitats richness and specially for their preservation of highly protected seagrass regions.