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. 2012:2:524.
doi: 10.1038/srep00524. Epub 2012 Jul 23.

Counting in the dark: non-intrusive laser scanning for population counting and identifying roosting bats

Suzanna Noor Azmy  1 , Shahrul Anuar Mohd Sah, Nur Juliani Shafie, Azman Ariffin, Zulkepli Majid, Muhamad Nor Akmal Ismail, Mohd Shahir Shamsir
Affiliations

Counting in the dark: non-intrusive laser scanning for population counting and identifying roosting bats

Suzanna Noor Azmy et al. Sci Rep. 2012.

Abstract

Population surveys and species recognition for roosting bats are either based on capture, sight or optical-mechanical count methods. However, these methods are intrusive, are tedious and, at best, provide only statistical estimations. Here, we demonstrated the successful use of a terrestrial Light Detection and Ranging (LIDAR) laser scanner for remotely identifying and determining the exact population of roosting bats in caves. LIDAR accurately captured the 3D features of the roosting bats and their spatial distribution patterns in minimal light. The high-resolution model of the cave enabled an exact count of the visibly differentiated Hipposideros larvatus and their roosting pattern within the 3D topology of the cave. We anticipate that the development of LIDAR will open up new research possibilities by allowing researchers to study roosting behaviour within the topographical context of a cave's internal surface, thus facilitating rigorous quantitative characterisations of cave roosting behaviour.

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Figures

Figure 1
Figure 1. The floor map of the Gua Kelawar showing the main cavern with the roosting bats.
The red dots represent the scanning stations, and the areas with the roosting bats are denoted in yellow.
Figure 2
Figure 2. The scanning points from different scanning stations are represented with different coloured points.
Figure 3
Figure 3. The ability to differentiate the presence of bats in the scan product.
A. The identification of bats' distributions in the scanned product based on difference reflectance values. B. The bats' population count. C. The parallel intersection of point cloud data.
Figure 4
Figure 4. Features used in the species identification of Hipposideros larvatus (image courtesy of Nick Baker; http://www.ecologyasia.com).
See this image and copyright information in PMC

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