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Computational Ecology and Software, 2011, 1(2): 95-111
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Use of geospatial technology in evaluating landscape cover type changes in Chandoli National Park, India

Ekwal Imam
Indian Institute of remote sensing, National Remote Sensing Agency, Dehradun, India
Current Address: Biology Department, College of Natural and Computational Science, Mekelle University, Mekelle, P.O. Box No. 231, Ethiopia

Received 31 March 2011; Accepted 25 April 2011; Published online 15 Junel 2011
IAEES

Abstract
Monitoring changes in landscape cover types has been a great concern for forest and wildlife managers. Both managers find it very important to know how much area is suitable for wildlife species and what areas are affected due to anthropogenic pressure. To address these concerns, evaluation of Chandoli National Park was done to see the changes that have taken place over the past 28 years. The National Park is situated in India lying within 170 04' 00" N to 170 19' 54" N and 730 40' 43" E to 730 53' 09" E. Remotely sensed data procured from satellite IRS-P6, LISS-III (2005) was used. The satellite data was digitally processed and collateral data were generated from topographic maps. The comparative analysis of topographic-map and imagery of 1977 and 2005 revealed that 120.9 km2 of evergreen forest has been lost during 28 years. Contrary to this an increase of 51.15 km2 in scrubland and 64.19 km2 in grasslands were noted. Furthermore, forest cover and land use maps of the study area were prepared from satellite data using supervised maximum likelihood classification technique. The study reveals that Park supports diversified habitats of scrubland (27.47%), grassland (20.13%), rejuvenated (22.17%) and evergreen forest (16.07%). The diversified cover types and improvement in forest density has made the Park suitable for wild animals than the previous one when it was not declared as protected area. The study advocates that if a forest area is protected and conserved from anthropogenic pressure may become more suitable for wild animals.

Keywords remote sensing; GIS; tiger; wildlife; landscape cover change; habitat suitability analysis; Chandoli National Park.



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