IRS-1C image data applications for land use/land cover mapping in Zagros region, Case study: Ilam watershed, West of Iran


Department of Forestry, Faculty of Agriculture, University of Ilam. Iran.


In land use planning, mapping the present land use / land cover situation is a necessary tool for determining the current condition and for identifying land use trends. In this study, in order to provide a land use/ land cover map for Ilam watershed, the IRS-1C image data from 25th April 2006 were used. Initial qualitative evaluation on data showed no significant radiometric error. Ortho-rectification of imagery was accomplished using ephemeris data, digital maps of topography and 45 ground control points with RMSe less than 0.7 pixels. Different suitable spectral transformations such as rationing, PCA, Tasseled Cap transformation were performed on the images in ILWIS software to enhance and produce new artificial images. Image classification was done using supervised classification maximum likelihood and minimum distance classifier utilizing original and synthetic bands resulted from diverse spectral transformation. Unsupervised classification was used to determine strata for ground truth. The results were assessed using a sample ground truth map through systematic random sampling and samples were designed in circle form and 1000m? area. Finally, nine main classes of land use / land cover (Rangeland, Forest (dense, semi-dense, sparse, very sparse), Agriculture, gardens, settlements and bare lands) could be determined. For representing accuracy, the rate was used from some criteria of accuracy such as overall accuracy and Kappa coefficient with 83% overall accuracy and 0.78 kappa coefficient.