Satellite image classification using proposed singular value decomposition method

Abstract

In this work, satellite images for Razaza Lake and the surrounding area district in Karbala province are classified for years 1990,1999 and 2014 using two software programming (MATLAB 7.12 and ERDAS imagine 2014). Proposed unsupervised and supervised method of classification using MATLAB software have been used; these are mean value and Singular Value Decomposition respectively. While unsupervised (K-Means) and supervised (Maximum likelihood Classifier) method are utilized using ERDAS imagine, in order to get most accurate results and then compare these results of each method and calculate the changes that taken place in years 1999 and 2014; comparing with 1990. The results from classification indicated that water and hills are decreased, while vegetation, wet land and barren land are increased for years 1999 and 2014; comparable with 1990. The classification accuracy was done by number of random points chosen on the study area in the field work and geographical data then compared with the classification results, the classification accuracy for the proposed SVD method are 92.5%, 84.5% and 90% for years 1990,1999,2014, respectivety, while the classification accuracies for unsupervised classification method based mean value are 92%, 87% and 91% for years 1990,1999,2014 respectivety.