Spatial and spectral variability due to Landsat image acquisition date: the impact on image classification

Large area land cover mapping with Landsat data is affected by differing image spectral characteristics caused by factors such as solar, radiometric, atmospheric, and phenologic conditions. For mapping land cover, especially forested land cover with single date satellite imagery, acquisition of imagery is ideally undertaken during the peak growing periods during the summer months. Yet, during the summer months cloud cover may preclude the collection of suitable imagery. To enable the collection of imagery to compile a large area coverage, the range of acceptable acquisition dates must be extended from the optimal mid-summer period. The question is how far can the acquisition dates range before the spectral information in the imagery is no longer appropriate for land cover mapping. To address this issue we have classified Landsat imagery representing a range of within year and between year dates and have assessed the variability in spatial features developed and the spectral information contained in the imagery. To ensure consistent radiometric characteristics between scenes we applied a top of atmosphere radiometric correction and a dark target subtraction. Our data set consists of 7 images. To assess within year variability we obtained 5 images over a range of dates within 1999.