CONTEXTUAL CORRECTION - TECHNIQUES FOR IMPROVING LAND-COVER MAPPING FROM REMOTELY-SENSED IMAGES

Large area land cover mapping is an important application of remote se nsing. A digital land cover map of Great Britain has recently been com piled by supervised classification of Landsat Thematic Mapper data. Th e work has involved development of a range of post classification proc edures to correct contextual errors associated with the use of spectra l classification algorithms. This paper describes these procedures and examines their effects upon the map product including a comparison wi th field survey data.