Contextual correction: techniques for improving land cover mapping from remotely sensed images

Abstract

Large area land cover mapping is an important application of remote sensing. A digital land cover map of Great Britain has recently been compiled by supervised classification of Landsat Thematic Mapper data. The work has involved development of a range of post classification procedures to correct contextual errors associated with the use of spectral classification algorithms. This paper describes these procedures and examines their effects upon the map product including a comparison with field survey data.