Observing the German Wadden Sea – A New Approach to Distinguish Sediments and Habitats Using Alos-2 Palsar-2 Data

Abstract

Quad-polarization Synthetic Aperture Radar (SAR) imagery can be well used to identify bivalve beds on dry-fallen intertidal flats and to investigate radar backscattering mechanisms on exposed sediments. In this study, a general classification approach to use spaceborne SAR data to distinguish sediment types, especially mud and sand, and to detect mussel beds, is presented. We propose a new feature set including Double-bounce Eigenvalue Relative Difference (DERD) and the Kennaugh elements, and combine those indicators with the unsupervised Wishart classifier. The main classification results of sediments and habitats agree with data from regular monitoring campaigns, which are frequently performed to fulfill the requirements of coastal environmental monitoring.