Habitat Suitability Modelling for Sambar (Rusa unicolor): A Remote Sensing and GIS Approach

Abstract

The concept of wildlife species conservation starts with the identification of their suitable habitat as it provides essential information for wildlife refuge design and management. In this study, multiple logistic regression is integrated with remote sensing and geographic information system to evaluate the suitable habitats available for sambar (Rusa unicolor) in Chandoli Tiger Reserve, Maharashtra, India (17 degrees 04' 00 `' N to 17 degrees 19' 54 `' N and 73 degrees 40' 43 `' E to 73 degrees 53' 09 `' E). Satellite imageries of LISS-III of IRS-P6 of study area were digitally processed. To generate collateral data topographic maps were analysed in a GIS framework. Layers of different variables such as land use land cover, forest density, proximity to disturbances and water resources and a digital terrain model were created from satellite imageries and topographic maps. These layers along with GPS location of sambar presence/absence and multiple logistic regression (MLR) techniques were integrated in a GIS environment to model habitat suitability index of sambar. The results indicate that approximately 69.92 km(2) (24 \%) of the forest of tiger reserve was least suitable for sambar, whereas 82.60 km(2) (28 \%) was moderately suitable, 88.25 km(2) (30 \%) suitable and 54.01 km2 (18 \%) was highly suitable. The accuracy level of this model was 80.2 \%. The model advocates that forests of this area are most appropriate for declaring it as a reserve for sambar conservation.