benefits of considering land cover seasonality in multi-spectral image classification
Effects of incorporating multi-seasonal information into image classifications for large-scale land cover mapping are investigated. Data from four Landsat7 ETM+ scenes (March, May, June 2002, September 1999) were included step-wise into classifications by discriminant analysis to document their relevance for classification accuracy. The classification using all four images reached a maximum accuracy of 69.2%, significantly higher compared with single-date classifications and showing less fluctuations in classification accuracy.