Conclusion |
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 water. Water bodies influence biophysical processes and energy exchanges between the atmosphere and the land surface as required by local and regional-scale climate and ecosystem process models. In this context, an important application of pattern classifiers would be to estimate accurate temporal land cover maps that are useful in monitoring the status of water bodies. The analysis showed that out of 265 water bodies in greater Bangalore in 1972, only 110 exist in 2007. The analysis showed a linear growth of 466% in number of urban pixels from 1973 to 2007 and a decline of 61% in the number of water bodies with a 63% decrease in vegetation cover in Greater Bangalore. Very few of them are in good condition and most of them are victims of encroachment, dumping yards and mismanagement. Appropriate policy decisions, interventions, and holistic approaches are required to restore them from degradation and achieve a sustainable environment.
