THE ACCURACY TEST OF SEVERAL IMAGE'S CLASSIFICATION METHODS USING ALOS AVNIR II IMAGE

Abstract

The identification of shallow-water surface objects needs special study for its identification processes. There are many methods that could be used for good identification in algorithm and classification model. This research was focused more in the classification method of the satellite images of ALOS AVNIR II. Method used was the Attenuated Lyzenga Method (ALM) with Re-class and image composite with Box Classification (parallelepiped), minimum distance to mean algorithm and maximum likelihood. The accuracy test and the determination of the model were best performed with the sign test and the kappa Test. Results of the previous research showed that Re-class from the ALM, and image composite 312 with classification method of minimum distance and maximum likelihood could be used for identification of the object of shallow-water surface; and the accuracy Test showed that image composite 312 with the classification method of maximum likelihood was the best model to be used in the identification of the shallow-water surface objects