Conclusion

  1. Spatio temporal dynamics analysis through the integration of multi temporal data offered an efficient way to examine forest spatial changes and fragmentation;

  2. Human induced changes shows 15.64% loss in the vegetation cover from 1973 to 2010;

  3. Land use analysis shows the degradation of deciduous forest cover from 56.23% to 47.93% due to human induced changes leading to fragmentation in the region;

  4. The landscape metrics analysis indicates of increase in the number of patches in the forest dominated areas that highlight the fragmentation of the vegetation cover. LPI index indicates that crop land has become dominant land use in the region. PARA_AM index shows complexity of the region in terms of shape because of alterations in the land cover;

  5. These results reveal that plane region is influenced by anthropogenic activities because of urbanization. The Sahyadri interior with undulating topography coupled with the effective conservation policies show nominal land use (buildings and agriculture) changes. The coastal region is more fragmented due to over exploitation of resources due to road accessibility. Thus, where densely distributed roads are present, forests are in peril;

  6. The prediction for 2020 indicates of 11.8% decline in forest cover (in the business as usual scenario) and 16.23% decline with the implementation of developmental projects and associated local land use changes;

  7. This work provides a valuable spatial insight into the trends in forest change and fragmentation with conservation implications for sustainable growth. Landscape analysis with incorporation of geographical and sociological perspectives, practical and theoretical approaches will help in tackling environmental problems.

Acknowledgement

The authors aregrateful to the Infrastructure Development Department (IDD), Government of Karnataka and NRDMS Division (DST), The Ministry of Science and Technology, Government of India and Indian Institute of Science for the financial and infrastructure support. The authors thank National Remote Sensing Centre, Hyderabad (http://www.nrsc.gov.in), for providing the IRS data.