Spatial search and a three level model based water layer extraction from C-band SAR image

ABSTRACT This paper describes a spatial search and a three-level model-based approach for automatic extraction of surface water layers from Sentinel-1 C-band SAR images at 10 m spatial resolution. The technique incorporates a connected component spatial search for segmenting low backscatter regions and uses the segmented image object for characterizing the segments. The water body is described here as a collection of different spatially connected segments. A three-level model is used to describe the connected segments of a water body in SAR data. Noise tolerance is achieved in this method by incorporating a speckle noise level into the model. The segmentation process further calculates contextual information which includes shadow estimated from DEM, polarization angle of the segment, and a boundary co-occurrence in both polarization to qualify the detected segments as a water body. The proposed method is found to have an accuracy of 94% in terms of f1 score. The algorithm, estimation of different parameters, and the results obtained in selected regions are explained in this paper.