Improved forest mapping by combining corrections of atmospheric and topographic effects in Landsat TM imagery

The spectral reflectance of ground objects in mountainous areas is largely contaminated by second order effects which are due to topographic slope and aspect. Such topographic effects present severe problem for the consistent analysis of optical remote sensing images, in particular for satellite-based forest cover mapping. We have integrated a topographic correction module into a modified 5S atmospheric correction model, where targets are assumed to have Iambertian reflectance characteristics. The method was successfully applied to four Landsat Thematic Mapper images with large seasonal differences in solar elevation. Classification methods of increasing complexity (euclidian minimum distance, maximum likelihood, and a backpropagation neural network) have then been used to produce forest stand maps from images which were either corrected for atmospheric effects only or for radiometric distortions due to both atmosphere and topography. It is demonstrated that the topographic corrections provide important improvements when direct and diffuse radiation components are properly accounted for. Differences between the actual bidirectional reflectance properties of forest stands and their approximation by Lambertian reflectance characteristics seem to be less important.