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Habitat Suitability Analysis for Swamp Deer (Rucervus Duvaucelii) Using Geo-Spatial Tools in Dudhwa National Park
American Journal of Remote Sensing
Volume 6, Issue 1, June 2018, Pages: 52-58
Received: May 15, 2018; Accepted: May 30, 2018; Published: Jul. 7, 2018
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Suneet Naithani, School of Environment and Natural Resources, Doon University, Dehradun, India
Prachee Bedi, School of Environment and Natural Resources, Doon University, Dehradun, India
Gopala Areendran, Indira Gandhi Conservation Monitoring Centre, World Wide Fund for Nature, New Delhi, India
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Dudhwa National Park (DNP), important conservation areas of India supporting the full range of threatened faunal and floral species. The Barasingha, swamp deer (Rucervus duvaucelii) considered as vulnerable, one of the flagship species. The satellite imagery of 1995, 2016 and 2017were used for Habitat Suitability Analysis (HSA) using multi-criteria analysis. The other primary and secondary data were also incorporated to generate habitat suitability model. Raster imageries of Landsat 5 and Landsat 8 were used to create various themes (variables) such as forest density, land use land cover, Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) along with topographic details. The result indicates that out of total geographical area approximately 2.000000-2.100000(20-21%) is highly suitable, 1.900000(19%) is appropriate, 1.800000(18%) moderately suitable, 1.700000(17%) less suitable and 1.500000-1.600000(15-16%) area is least suitable. However, the study strongly advocates that the DNP is suitable landscape and grassland were noticed as one of the best habitat class for the conservation of swamp deer.
Dudhwa National Park (DNP), Swamp Deer, Habitat Suitability Analysis (HAS), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI)
To cite this article
Suneet Naithani, Prachee Bedi, Gopala Areendran, Habitat Suitability Analysis for Swamp Deer (Rucervus Duvaucelii) Using Geo-Spatial Tools in Dudhwa National Park, American Journal of Remote Sensing. Vol. 6, No. 1, 2018, pp. 52-58. doi: 10.11648/j.ajrs.20180601.18
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This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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