A comparative study of supervised classifiers on a subscene in Junagadh district, Gujarat
- 26 Downloads
This paper describes the results of a comparative study of five classifiers viz., maximum likelihood, modified maximum likelihood, minimum distance to mean. Fisher and min-max, for classifying a subscene of Junagadh district using Landsat Thematic Mapper (TM) data. The kappa coefficient of agreement (k) and per cent correctly classified pixels for training data are used as measures of overall performance. It is observed that maximum likelihood and modified maximum likelihood classifiers perform better than the other three classifiers for this data set. Band combinations (3, 4, S) and (2, 3, 4, S) perform better than the usual combination (1,2,3,4), possibly because of presence of middle infrared band (band 5) on a scene dominated by vegetation cover. The band combination (1, 2, 3, 4, 5, 7) performed the best.
Unable to display preview. Download preview PDF.
- Beaubien J 1979. Forest type mapping from Landsat digital data.Photogr. Engg. and Rem. Sens.,45, 1135–1144.Google Scholar
- Chang J K and Dwyer S J, 1973. New multiclass classification method : Modified maximum likelihood decision rule.Proceedings of the first International Joint Conference on Pattern Recognition. Washington D.C., October 30–November 1, 334–339.Google Scholar
- Craig R G. 1979. Autocorrelation in Landsat data.Proceedings of the 13th Int. Symp. on Rem. Sens. Environment, Ann Arbor, Michigan, 1517–1524.Google Scholar
- Craig R G and Labovitz M L 1980. Sources of variation in Landsat autocorrelation,Proceedings of the 14th Int. Symp. on Rem. Sens, of Environment. Ann Arbor, Michigan, 1755–1767.Google Scholar
- Dadhwal V K, Parihar J S, Medhavy D S, Ruhal D S and Jarwal S D 1987. Wheat acreage estimation of Haryana for 1986–87, using Landsat MSS data.Scientific Note : IRS-UP/SAC/CPF/SN/ 15/87, 26.Google Scholar
- Hudson W D and Ramm C W 1987. Correct formulation of the kappa coefficient of agreementPhotogr. Engg. and Rem. Sens.,53, 421–422.Google Scholar
- Jenson JR 1986.Introductory digital image processing: a remote sensing perspective. Prentice-Hall, New Jersey.Google Scholar
- Nelson R F, Latty R S and Mott G, 1984. Classifying northern forests using Thematic Mapper Simulator data.Photogr. Engg. and Rem. Sens.,50, 607–617.Google Scholar
- Potdar M B, Kalubarme M H, Sharma R, Biswas B C, Dubey RC and Bhandari S G 1987. Remote sensing based hectarage estimation of semi-arid tropical crops : A case study of 1986 rabi sorghum in Solapur district.Scientific Note: IRS-UP/SAC/CPF/SN/14/87. 23p.Google Scholar
- Rosenfield G H and Fitzpatrick-Lins R 1986. A coefficient of agreement as a measure of thematic classification accuracy,Photo. Engg. and Rem. Sens,52, 223–227.Google Scholar
- Sheffield C 1985. Selecting band combinations from multispectral data.Photogr. Engg. and Rem. Sens.,51, 681–687.Google Scholar
- Skidmore A K and Turner B J 1988. Forest mapping accuracies are improved using a supervised nonparametric classifier with SPOT data.Photogr. Engg. and Rem. Sens.,54, 1415–1421.Google Scholar