An experimental analysis has been conducted on the performance of the new LANDSAT-5 Thematic Mapper (TM) data for detailed land-cover classification using a maximum-likelihood method. Data used is the TM test data of the Tokyo metropolitan area (path-107, row-035) of 4 November, 1984. Map-precision geometric correction is performed and TM data are resampled to 30  m pixel spacing. The experiment is designed to determine how well TM categories land-cover types in comparison with the Detailed Numerical Information digitally formatted data (Geographical Survey Institute of Japan, 10  m spatial accuracy), together with ground truth data in a representative test area. Classification accuracy for aggregated 12 categories within the test area is about 47 per cent with the application of the explicit filtering technique utilizing 3×3 neighbourhood operations. This increases to 70 per cent using a majority logic filter with a larger 5×5 neighbourhood function. Associated with the classification accuracy, effects of the mixed pixels are also investigated. The results show that the improved characteristics of TM aided the overall classification accuracy.