Land use/cover classification using enhanced IRS-1A LISS 1 data — A case study of Calcutta Metropolitan District,India — 1989

The land use/cover in any urban area is dynamic in nature. Maps of existing land use/covers have to be updated periodically to monitor changes. To speed up mapping and decision making, remotely sensed satellite data have been advocated. This study used the IRS-1A LISS 1 satellite data for delineation of selected urban features in Calcutta Metropolitan District. Due to lack of ground information, some known features have been used as reference categories to classify the study area.The satellite data was transformed through a principal components analysis and two new bands of data were created and combined with the original four band data. Both supervised and unsupervised methods were used for spectral signature collection. Thirty-six classes derived from Isodata clustering, after comparing with the selected known features, these were grouped to form five generalized land use/cover categories. The spatial distribution of these land use/cover categories have been explained in this study.