Abstract
Multispectral band remote sensing imagery is used for environmental monitoring and land use and land cover mapping purposes. This image contains huge volume of data. Instead of using the entire data for land use land cove mapping, the spatially compressed images can also be used for mapping purposes. In this paper discrete wavelet transform is selected for compressing the Landsat5 image and the quality has been analysed using the parameters compression ratio, peak signal to noise ratio and digital number values. Using the digital number values the spectral signature graph is drawn. Finally only one wavelet is selected for land use and land cover mapping based on minimum cumulative error of the digital number values. Then the selected wavelet compressed image is classified using supervised classification technique and accuracy assessment is made by constructing the error matrix. Finally the selected wavelet compressed image is used for land use and land cover mapping. Keywords: Compression Ratio (CR), Peak Signal to Noise Ratio (PSNR), Digital Number (DN), Image Classification, Error Matrix, Spectral Signatures.
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