Land classifier using parallel minimum vector variance method

To provide accurate land classification, we need to have a good and robust estimators. Minimum Vector Variance (MVV) is one of the robust method to produce them. In this paper, we implement the method to classify absorption land in Jakarta province. Our Experiment using 2002's satelite images of Jakarta area (band 1, 2, 3 and 4) has shown that MVV methods provides good classification of less than 5%. We also decreased the process time in order to occupy various types of land classification by enabling parallel technique on the solution. The experiment shows an average speedup almost two times of the sequential process of classyfing 2002's satelite images of Jakarta.