Application of the Decomposition of Mixed Data in Remotely Sensed Images.

概要

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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 of 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 prior probabilities of landcovers in seven 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.
社団法人日本写真測量学会の論文