Imam EKWAL*1, Hussain TAHIR2, Mary TAHIR3
* Corresponding author
1 Mekelle University, Department of Biology, Corresponding author, Mekelle, ETHIOPIA
2 Mekelle University, Department of Geography & Environmental Studies, Mekelle, ETHIOPIA
3 Jamia Millia Islamia University, Department of Geography, New Delhi, INDIA
E-mail: ekwalimam@rediffmail.com, ekwalimam01@gmail.com
Pages: 93-102. URL: https://geografie.ubbcluj.ro/ccau/jssp/arhiva_2_2012/04JSSP022012.pdf
Cite: Ekwal I., Tahir H., Tahir M. (2012), Modelling of Habitat Suitability Index for Muntjac (Muntiacus muntjak) Using Remote Sensing, GIS and Multiple Logistic Regression. Journal of Settlements and Spatial Planning, 3(2), 93-102. URL: https://geografie.ubbcluj.ro/ccau/jssp/arhiva_2_2012/04JSSP022012.pdf
Abstract. Habitat degradation and loss has been widely recognized as the main cause for the decline of wildlife population. Evaluating the quality of wildlife habitat can provide essential information for wildlife refuge design and management. The purpose of this study was to produce georeferenced ecological information about suitable habitats available for muntjac, Muntiacus muntjak in Chandoli tiger reserve, India (17°04’00” N to 17°19’54” N and 73°40’43” E to 73°53’09” E). Habitats were evaluated using multiple logistic regression integrated with remote sensing and geographic information system. 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 Landuse land cover, forest density, proximity to disturbances and water resources and a digital terrain model were created from satellite and topographic sheets. These layers along with GPS location of muntjac presence/absence and ―multiple logistic regression (MLR) techniques were integrated in a GIS environment to model habitat suitability index of muntjac. The results indicate that approximately 222.39 km2 (75.4%) of the forest of tiger reserve was least suitable for muntjac, whereas, 29.53 km2 (10.02%) was moderately suitable, 22.12 km2 (7.5%) suitable and 20.70 km2 (7.0%) was highly suitable. The accuracy level of this model was 97.6%. The model can be considered as potent enough to advocate that forests of this area are most appropriate for declaring it as a reserve for muntjac conservation, ultimately to provide prey base for tiger.
K e y w o r d s: Muntjac, habitat suitability index, multiple logistic regression, modelling, remote sensing