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

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 co...

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Bibliographic Details
Published in:International journal of remote sensing 1996, Vol.17 (1), p.69-89
Main Authors: GROOM, G. B., FULLER, R. M., JONES, A. R.
Format: Article
Language:English
Subjects:
Agronomy. Soil science and plant productions
Animal, plant and microbial ecology
Biological and medical sciences
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Generalities. Biometrics, experimentation. Remote sensing
Remote sensing
Teledetection and vegetation maps
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Summary: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.
ISSN:0143-1161
1366-5901
DOI:10.1080/01431169608948987