Abstract
Evaluations of landcover classification characteristics for Landsat TM and SPOT HRV data were performed. Three kinds of classification experiments using the most popular supervised maximum likelihood classifier were conducted. The first one is an assessment of effects of higher spatial resolutions, in which images of several ground resolutions (20m-75m) were classified. The purpose of the second experiment is to clarify the usefulness of higher spectral resolution of TM data. In this experiment, several band combinations were tested. The last one is the evaluation of spatial feature characteristics. Four kinds of texture features were extracted from co-occurrence matrices, and the effectiveness of those features for a landuse classification were evaluated.As a result, the following conclusions were obtained. The addition of new spectral bands, i.e. band 1, 5 and 7 in TM has introduced a little increase in the landcover classification accuracy. The increase of spatial resolutions does not necessarily provide higher classification accuracies. This fact indicates that some kinds of spatial informations should be utilized to obtain higher accuracies. However, a simple addition of texture features to spectral features could not increase the classification accuracy.
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