The influence of filtration and decomposition window size on the threshold value and accuracy of land-cover classification of polarimetric SAR images

First, we processed a fully polarimetric Synthetic Aperture Radar SAR L-band image using different sizes of speckle filtration and decomposition window 3 × 3 pixels, 5 × 5, 7 × 7, 9 × 9, and the decomposition methods available in PolSARPro software. We evaluated these methods and chose the most efficient. Then we developed a simple hierarchical classification scheme based on threshold values. In the first step we divided the terrain into smooth and rough areas and then separated these into more detailed subclasses water and agriculture, and forest and urban which correspond to smooth and rough areas, respectively. A more detailed analysis separated continuous and discontinuous urban fabric and deciduous and coniferous forests. The maximum overall accuracy of the classification was 86.1% for the four main land cover classes, and 80.4% for the six more detailed classes. The accuracy of the classification dropped by about 10% when non-optimal window sizes were used in image filtration or decomposition.