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Optimum spatial resolution of satellite based optical sensors for maximizing classification performance is investigated. Also, classification performance assessment method considering spatial resolution of satellite based optical imagers is proposed. Optimum spatial resolution which makes the highest classification accuracy is determined from spatial frequency components, spectral features of objects and classification method. First, in this paper, based on the relationship between variance of pixels and classification accuracy, classification accuracy for Landsat Multiple Spectral Scanner: MSS images with various Instantaneous Field of View (IFOV) will be shown. In their connection, variance of pixel values for images with various IFOV will be clarified. Second, assuming the shape of boundary line between adjacent categories is circle, relationship among IFOV, ratio of Mixels and classification accuracy will be cleared under the supposition that the number of Mixels equals to that of misclassified pixels. Finally, it will be also shown that aforementioned relationships and optimum spatial resolution have been confirmed by using airborne based MSS data of Sayama district in Japan. Keywords—Spectral information; spatial information; maximum likelihood decision rule; satellite image; image classification; mixed pixel (Mixels); optimum spatial resolution; classification performance; spatial and spectral features

Optimum Spatial Resolution of Satellite-based Optical Sensors for Maximizing Classification Performance