Upscaling aspects of multi-resolution satellite data in spatial and frequency domains Original Research Article

To incorporate intelligence from NOAA/AVHRR data for defining land surface boundary in GCMs, 1.1 km resolution data have to be upscaled to 50 or 100 km. The 36.25 m resolution LISS-II data was upscaled to 72.5 m and then correlation of this upscaled 72.5 m data was studied with the observed 72.5 m resolution LISS-I data. Research results reported in this paper address to the preservation of maximum information content in the upscaled data by reducing the impact of random noise component during upscaling process. For frequency domain upscaling, 72.5 m upscaled image was obtained from 36.25 m resolution IRS LISS-II data by (i) removing high frequency component in Fourier Transform of the 36.25 m resolution image and thereafter performing inverse Fourier Transform and (ii) after applying mean, median, k-average, mode and fractal operators on the image. This method gave very high correlations with LISS-I image even in heterogeneous regions and thus holds high promise in handling the heterogeneity, which occurs in 50×50 or 100×100 square km grids over land surface. This paper also addresses to upscaling of 188 m resolution NDVI derived from WiFS data to 1100 m and its correlation with 1100 m resolution NDVI derived from AVHRR.