Wildlife habitat analysis for ‘sambar’ (Cervus unicolor) in Kanha National Park using remote sensing

Porwal, M. C.; Roy, P. S.; Chellamuthu, V.

doi:10.1080/01431169608949100

Cited by 34 publications

(18 citation statements)

References 2 publications

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“…Conversely, for Sambar vegetation and terrain seem to be more suitable at XN compared to GM as described by Porwal et al (1996) and Varni et al (2012) while nothing is known about the reaction of sambar to human disturbance. At the NRWNNR, no open or half-open patches were found in the forest, which are often described as preferred ungulate habitat in Southeast Asia (Chodhury, 2002;Eisenberg and Seidensticker, 1976;Wani et al, 2012).…”

Section: Wildlife Species Abundancementioning

confidence: 91%

Wild Ungulate Distribution in the Naban River Watershed National Nature Reserve, Southwest China

Treydte

Trumpf

Langenberger

et al. 2014

JTFE

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Southeast Asia´s tropical forests harbour a unique diversity of wildlife but species and numbers are rapidly declining under current land use. To improve conservation strategies in these biodiversity hotspots, knowledge of animal species present and their distribution is crucial. We wanted to identify the ungulate community composition and distribution of a 'Man and Biosphere' reserve, the Naban River Watershed National Nature Reserve (NRWNNR), Yunnan, Southwest China. Using camera traps, transects, and spoorplots we identified wild ungulate species and corresponding habitat properties. We compared two study sites of different protection status -the buffer and experimental zones -on an overall transect length of 32 km and analysed relationships between wildlife activity, forest vegetation structure, and human disturbance. We documented six ungulate species, all of which occurred in the buffer zone while only three species were found in the experimental zone. Wild boar sign density was about 10 times higher in the buffer than in the experimental zone. Overall wildlife sign density increased with distance away from human settlements and closer to the core zone. Hence, human disturbance strongly influenced wild ungulate abundance but the NRWNNR was found to host a diverse ungulate community, considering its small size and compared to other conservation areas in the region. The combination of various methods proved to be successful in identifying and locating forest wildlife. The NRWNNR, particularly the more strongly protected zones, could greatly contribute to future ecotourism activities in Yunnan if a strict preservation of buffer and core zones can be maintained.

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Section: Wildlife Species Abundancementioning

confidence: 91%

Wild Ungulate Distribution in the Naban River Watershed National Nature Reserve, Southwest China

Treydte

Trumpf

Langenberger

et al. 2014

JTFE

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“…In 1986, Parihar et al evaluated habitat of Indian one-horned rhinoceros using remotely sensed data from 'LANDSAT', while Roy et al (1995) used this technology for habitat suitability analysis of Nemorhaedus goral. Similarly Porwal et al (1996) analyzed suitable habitat for sambar (Cervus unicolor) in Kanha National Park using RS data. The geospatial technology was widely used by Kushwaha and his colleagues for habitat suitability analysis of various wild animals.…”

Section: Use Of Geospatial Technology For Analysis Of Habitat Suitabimentioning

confidence: 99%

Habitat suitability modelling for Gaur (Bos gaurus) using multiple logistic regression, remote sensing and GIS

Imam

Kushwaha

2013

Journal of Applied Animal Research

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The aim of this study is to produce georeferenced ecological information about the suitable habitats available for gaur Bos gaurus in Chandoli tiger reserve, India (178 04? 00ƒ N to 178 19? 54ƒ N and 738 40? 43ƒ E to 738 53? 09ƒ E). Habitat suitability index (H.S.I.) was developed using multiple logistic regression (MLR) integrated with remote sensing (RS) and geographic information system (GIS). Satellite imageries of study area, acquired from Indian remote sensing satellite-P6, linear imaging self-scanning satellite-III of 2005, was digitally processed, whereas topographic maps were used for generating the collateral data in a GIS framework. Various layers of different variables such as forest density, Landuse land cover, measures of proximity to disturbances and water resources and a digital terrain model were created from satellite and topographic data. These layers along with global positioning system location of gaur presence/absence and MLR technique were integrated in a GIS environment for modelling the H.S.

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“…In addition, habitat development activities like canopy opening of plantation forests, controlled burning of grassland, removal of overwood from grassland and plantation of grasses also introduces dynamic changes in the extent of foraging areas of rhino. Considering the difficulties encountered while making manual assessment of the grassland and forest composition, on frequent basis, Remote sensing technology is found to be the most suitable tool for monitoring the habitat changes on real time basis [2,6,[9][10][11]12,13,15,18,19] . …”

Section: Objective Of the Study 1) To Prepare Vegetation Maps Ofmentioning

confidence: 99%

Time Series Study of Rhino Habitat and its Impact on Rhino Population in Gorumara National Park through Remote Sensing Technology

Ghatak¹,

Bhutia²,

Mitra³

et al. 2016

IJEAB

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Wildlife habitat analysis for ‘sambar’ (Cervus unicolor) in Kanha National Park using remote sensing

Cited by 34 publications

References 2 publications

Wild Ungulate Distribution in the Naban River Watershed National Nature Reserve, Southwest China

Wild Ungulate Distribution in the Naban River Watershed National Nature Reserve, Southwest China

Habitat suitability modelling for Gaur (Bos gaurus) using multiple logistic regression, remote sensing and GIS

Time Series Study of Rhino Habitat and its Impact on Rhino Population in Gorumara National Park through Remote Sensing Technology

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