Posidonia oceanica is the dominant seagrass in the Mediterranean Sea that affects biological, biogeochemical and physical processes in Mediterranean coastal areas. The widespread loss of this species is attributed to excessive anthropic pressure and other large-scale environmental changes. Seagrass conservation requires mapping to estimate the extent of existing stocks and to measure changes over time. Optical remote sensing provides a cost-effective method to monitor vast areas of shallow waters that are potential P. oceanica habitat. As part of an interdisciplinary research effort, where the effects of these seagrasses on the hydrodynamics were investigated, new technologies of reliable, fast and effective monitoring of P. oceanica were essential. This paper presents a method for using IKONOS multispectral imagery for bottom classification in a shallow coastal area of Mallorca (Balearic Islands). After applying a supervised classification, pixels are automatically classified in four classes: sand, rock, P. oceanica bottoms and unclassifiable pixels. Results indicate that, in these clear waters, the spectral response of P. oceanica can be determined to a depth of about 15 m. In order to validate the method, the image classification is compared with a bottom classification derived from an acoustical survey. Agreement with the reference acoustic seabed classification is up to 84% for the sampled area. Spectral IKONOS image analysis is presented as an effective approach for monitoring P. oceanica meadows in most clear, shallow waters of the western Mediterranean. © 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

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