Potential of RapidEye image data for sediment monitoring of the German tidal flats

The Wadden Sea is located in the southeastern part of the North Sea forming an extended intertidal area along the Dutch, German and Danish coast. It is a highly dynamic and largely natural ecosystem influenced by climatic changes and anthropogenic use of the North Sea. Changes in the environment of the Wadden Sea, natural or anthropogenic origin, cannot be monitored by the standard measurement methods alone, because large-area surveys of the intertidal flats are often difficult due to tides, tidal channels and unstable underground. For this reason, remote sensing offers effective monitoring tools. In this study a multi-sensor concept for classification of intertidal areas in the Wadden Sea has been developed. Basis for this method is a combined analysis of RapidEye (RE) and TerraSAR-X (TSX) satellite data coupled with ancillary vector data about the distribution of vegetation, mussel beds and sediments. The classification of the vegetation and mussel beds is based on a decision tree and a set of hierarchically structured algorithms which use object and texture features. The sediments are classified by an algorithm which uses thresholds and a majority filter. Further improvements focus on radiometric enhancement and atmospheric correction. First results show that we are able to identify vegetation and mussel beds with the use of multi-sensor remote sensing. The classification of the sediments in the tidal flats is a challenge compared to vegetation and mussel beds. The results demonstrate that the sediments cannot be classified with high accuracy by their spectral properties alone due to their similarity which is predominately caused by their water content.

Benthic and substrate cover data derived from photo-transect surveys in Heron Reef

Underwater georeferenced photo-transect survey was conducted on September 23 - 27, 2007 at different sections of the reef flat, reef crest and reef slope in Heron Reef. For this survey a snorkeler or diver swam over the bottom while taking photos of the benthos at a set height using a standard digital camera and towing a surface float GPS which was logging its track every five seconds. A standard digital compact camera was placed in an underwater housing and fitted with a 16 mm lens which provided a 1.0 m x 1.0 m footprint, at 0.5 m height above the benthos. Horizontal distance between photos was estimated by three fin kicks of the survey diver/snorkeler, which corresponded to a surface distance of approximately 2.0 - 4.0 m. The GPS was placed in a dry-bag and logged its position as it floated at the surface while being towed by the photographer. A total of 3,586 benthic photos were taken. A floating GPS setup connected to the swimmer/diver by a line enabled recording of coordinates of each benthic. Approximation of coordinates of each benthic photo was done based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software (www.geospatialexperts.com). Coordinates of each photo were interpolated by finding the gps coordinates that were logged at a set time before and after the photo was captured. Benthic or substrate cover data was derived from each photo by randomly placing 24 points over each image using the Coral Point Count excel program (Kohler and Gill, 2006). Each point was then assigned to 1 out of 80 cover types, which represented the benthic feature beneath it. Benthic cover composition summary of each photo scores was generated automatically using CPCE program. The resulting benthic cover data of each photo was linked to gps coordinates, saved as an ArcMap point shapefile, and projected to Universal Transverse Mercator WGS84 Zone 56 South.