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Curve Number Estimation for Watershed using Digital Image of IRS-1D LISS-III
Landuse/landcover classification map
The digital image (IRS-1D LISS-III) of the watershed was registered with the original satellite scene and the mask of the image was prepared. The enhancements and Histogram Equalization were applied to further processing of image. False color composite (FCC) of the scene was prepared and multispectral classification of image data was carried out applying supervised classification using ERDAS IMAGINE-8.4 software. Maximum Likelihood Classifier (MLC) algorithm was used for classification of the land use. MLC is based on the estimated Gaussian probability density functions for each of the reference classes. Overall accuracy of classification and Kappa Coefficient was found to be 86.950 % and 0.88 respectively. Maximum likelihood report for land use classification for watershed and classified output of the image is presented in Table 1 and Fig. 2 respectively.  Figure 2 Land use map of watershed
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