A Semi-Automatic Approach for the Extraction of Sandy Bodies (Sand Spits) From IKONOS-2 Data

The automatic or semi-automatic extraction of features from satellite images has always become a challenge for remote sensing researchers. The analysis of satellite imagery of natural scenes presents many unique problems, because they cannot be represented easily by regular rules or grammars. A sand spit does not present a well-defined topographic boundary, because they are influenced by tides, waves and wind. Moreover, the bubbles and foam caused by the breaking waves and the turbidity of the water difficult an accurate extraction of the boundary between land (sand spit) and water. This paper presents different approaches in order to extract sand spits from IKONOS-2 data. A novel semi-automatic approach is proposed, which is based on global thresholding through the Otsu's method, further refined through detected edges (GThE). The performance of GThE is compared with traditional pixel-based and object-based classification algorithms. The dataset is composed by six IKONOS-2 images, acquired between 2001 and 2007, covering a sand spit (Cabedelo) located in Portugal. The performance of the three methods used in the estimation of the sand spit area was evaluated through two sets of reference values of the sand spit area. The proposed GThE method presented better results than the other traditional methods, with a clear advantage of a considerable faster performance, beyond requiring a minimum operator intervention. Finally, the relation of the sand spit area with several hydrodynamic and agitation parameters was investigated, where it was demonstrated that the river discharge was the parameter with higher influence in the Cabedelo area.