Imaging spectroscopy as a tool to study sediment characteristics on a tidal sandbank in the Westerschelde

This paper focuses on the use of imaging spectroscopy for the mapping of sediment characteristics on a tidal sandbank in the Westerschelde, called the Molenplaat. On June 8, 2004, during low tide, a HyMap scanner recorded the Molenplaat at 4 m pixel resolution. The hyperspectral data were radiometrically calibrated, geometrically corrected, and atmospherically corrected to give apparent surface reflectance data. On the calibrated and corrected dataset a supervised binary classification was performed, based on linear discriminant analysis. Simultaneous to the flight, 25 sediment samples were collected in the field and analysed in the lab to define the median grain size, the water content, the total organic matter content and the chlorophyll-a concentration. These four parameters play a crucial role in sediment stability and macrofaunal habitat definition. Prior to the classification, a feature selection, based on sequential floating forward search (SFFS), was performed. For each of the four parameters two to three bands were retained for the classification. These bands were most frequently selected in the visible and near infrared parts of the spectrum, except for the organic matter content where also SWIR bands were used. The overall classification accuracy was highest for the water content (88%), the median grain size (88%) and the chlorophyll-a concentration (84%). The organic matter content, for which three instead of two classes were distinguished, scored somewhat lower but still reached 80%. The classifications were limited to a small number of classes in order to obtain reliable statistics with a small number of training samples. The spatial patterns in the classified images indicated that the four parameters under study are highly correlated. In most cases coarse sediment coincided with dry conditions, low organic matter and low concentrations of chlorophyll-a. The wet and muddy parts of the Molenplaat were in general characterised by a notably higher amount of organic matter and chlorophyll-a. The individual classification results for the median grain size, the water content and the chlorophyll-a concentration were combined to generate a sediment ecotope map. The presented study illustrates how airborne hyperspectral data can be used to achieve accurate classified maps of intertidal sediment ecotope types, applying feature selection and a binary classification approach