CONCLUSION

The study indicated that HPM is most suitable technique for merging IRS MS and PAN images. COS is best for fusing 1:2 Landsat ETM+ PAN and MS bands. HP Filter performed best on the fusion of 1:50 and 1:100 resolution ratio data. Visual appearance of fused images (IKONOS PAN and MODIS, 1:250 and 1:500) did not bring any sharpness and one may not see significant improvement in the pixel’s appearance before and after image fusion. However, statistical properties of the fused images revealed that HP Filter retained all the properties after fusion. It may be concluded that fusion of high and moderate spatial resolution MS band with HSR PAN band retains the spatial and spectral properties of the fused bands. However, as the spatial resolution decreases, fusion of images does not facilitate image quality enhancement for object identification. In such cases, spectral unmixing techniques can be employed on low spatial resolution data.

Pattern classifiers along with the advances in geo-informatics coupled with the availability of higher spatial, spectral and temporal resolution data help in extracting spatial features of interest like land cover classes such as wetlands. In this context, an important application of pattern classifiers would be to accurately estimate the spatial extent of temporal wetlands that are useful in monitoring their status. The analysis showed that the number of wetlands declined by 61% in Greater Bangalore. The city administration needs to improvise upon the growth model so that the city caters not only to the growing needs of the population but also restore and maintains the natural assets from further degradation and achieve a sustainable environment.