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Type: Journal article
Title: Using satellite imagery to assess the distribution and abundance of southern hairy-nosed wombats (Lasiorhinus latifrons)
Author: Swinbourne, M.
Taggart, D.
Swinbourne, A.
Lewis, M.
Ostendorf, B.
Citation: Remote Sensing of Environment, 2018; 211:196-203
Publisher: Elsevier
Issue Date: 2018
ISSN: 0034-4257
Statement of
Michael J. Swinbourne, David A. Taggart, Alyce M. Swinbourne, Megan Lewis, Bertram Ostendorf
Abstract: Monitoring of the southern hairy-nosed wombat (Lasiorhinus latifrons) population via satellite imagery was first proposed in 1980. However, the imagery that was available at that time was inadequate for the task as it did not permit the direct observation and counting of warrens. Since then, advances in the availability and resolution of satellite imagery mean that it is now possible to map the entire distribution of southern hairy-nosed wombats and to estimate their population abundance using very high-resolution imagery (≤1.0 m). However, other landscape features such as rabbit warrens can make the identification of wombat warrens problematic, and not all wombat warrens are visible, even in the best resolution imagery. By comparing data that we collected from field surveys conducted between May 2015 – May 2017 with satellite imagery we could identify that many wombat warrens have visible trails linking warrens with each other. Whilst this allowed us to differentiate between wombat and rabbit warrens in most circumstances, the lack of visible trails in some instances highlighted the need for ground truthing surveys to be conducted as part of any broad scale wombat population survey. Based on the difference between the number of warrens that we marked during our ground surveys with the number which were visible in the satellite imagery, we calculated a range of indices which can be used to correct future broad-scale population estimates based on satellite imagery, to account for warrens which may be obscured by vegetation and other confounding factors.
Keywords: Burrowing; distribution; satellite imagery; limitations
Rights: © 2018 Elsevier Inc. All rights reserved
RMID: 0030086789
DOI: 10.1016/j.rse.2018.04.017
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Appears in Collections:Environment Institute publications

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