Land use classification with textural analysis and the aggregation technique using multi-temporal JERS-1 L-band SAR images

This paper describes a method of improving classification accuracy when using Synthetic Aperture Radar (SAR) images. The classifier used is a maximum likelihood classifier. Texture and textural feature images were made and used for classification. The accuracy of various classification methods was compared. As a result, it was found that the best classification was produced by the aggregation of the classified image when using texture images as additional inputs to the classifier. It is also shown that textural analysis and the aggregation technique are useful in the classification of SAR images.