抄録
A priori probabilities of landcover categories in the study area improve the landcover classification accuracy, although the probabilities are very difficult to estimate in advance before the analysis. Algorithms for the decomposition of mixels to pure landcover categories were developed to estimate landcover area ratios in mixels. If the study area is supposed to be a very large mixel which contains several landcover categories, some of the decomposition algorithms of mixed data can be applied to the centroid vector of the study area. The area ratios of landcovers in the study area are equal to the a priori probabilities of landcovers.
The algorithm of maximum likelihood estimation was applied to estimate the a priori probabilities of landcovers in the study area in this research. As a result of this research, the estimation algorithm worked well and the a priori probabilities of landcovers in small study sites were estimated very well. Moreover, those estimated a priori probabilities of landcovers improved the accuracy of landcover classification in the study sites, comparing with the classification results of the maximum likelihood classifier, the Bayes' classifier with actual a priori probabilities and the italation of the maximum likelihood classifier.
