Predicting the distribution of Eastern Grey Kangaroos by remote sensing assessment of food resources.

Rollings, Nicholas and Moss, Graeme (2016) Predicting the distribution of Eastern Grey Kangaroos by remote sensing assessment of food resources. Journal of Biological Sciences, 2 (11). pp. 26-56. ISSN 2455-7676

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Abstract

This study demonstrates how the distribution of animals can be described using remotely sensed data at a scale in the order of square kilometers. Kangaroo distribution has been monitored at regional scales using aerial surveys and detailed field study. This study attempts to fill the gap between local and regional scales by using Landsat derived vegetation characteristics to provide animal distribution details at local scale. Field surveys of Eastern Grey kangaroos and vegetation biomass were undertaken at the Warrumbungle National Park, New South Wales, Australia. The distribution and abundance of kangaroos and plant biomass were compared with remotely sensed vegetation characteristics taken from Landsat TM imagery. The distribution of green, short (< 5cm) blade grass biomass (the preferred kangaroo food resource) was patchy and positively correlated with kangaroo density and Landsat spectral bands 1, 2, 3 and a principal component combination of bands 1-7 (excluding band 6). Total population density was positively correlated with blade grass biomass and Landsat band 3. The dispersion of kangaroos within habitats was patchy, even though the Landsat image defined habitats as being homogeneous. This study clearly demonstrates the value of Landsat data to environmental management in the past and present.

Item Type:	Journal Article
Subjects:	G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > QH Natural history > QH301 Biology Q Science > QL Zoology
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Geography, Earth Science and Environment
Depositing User:	Nicholas Rollings
Date Deposited:	03 Sep 2017 22:07
Last Modified:	16 Oct 2023 00:40
URI:	http://repository.usp.ac.fj/id/eprint/10097

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