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Counting in the dark: Non-intrusive laser scanning for population counting and identifying roosting bats
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 D...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3401962/ https://www.ncbi.nlm.nih.gov/pubmed/22826802 http://dx.doi.org/10.1038/srep00524 |
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author | Azmy, Suzanna Noor Sah, Shahrul Anuar Mohd Shafie, Nur Juliani Ariffin, Azman Majid, Zulkepli Ismail, Muhamad Nor Akmal Shamsir, Mohd Shahir |
author_facet | Azmy, Suzanna Noor Sah, Shahrul Anuar Mohd Shafie, Nur Juliani Ariffin, Azman Majid, Zulkepli Ismail, Muhamad Nor Akmal Shamsir, Mohd Shahir |
author_sort | Azmy, Suzanna Noor |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3401962 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-34019622012-07-23 Counting in the dark: Non-intrusive laser scanning for population counting and identifying roosting bats Azmy, Suzanna Noor Sah, Shahrul Anuar Mohd Shafie, Nur Juliani Ariffin, Azman Majid, Zulkepli Ismail, Muhamad Nor Akmal Shamsir, Mohd Shahir Sci Rep Article 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. Nature Publishing Group 2012-07-23 /pmc/articles/PMC3401962/ /pubmed/22826802 http://dx.doi.org/10.1038/srep00524 Text en Copyright © 2012, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-sa/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareALike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ |
spellingShingle | Article Azmy, Suzanna Noor Sah, Shahrul Anuar Mohd Shafie, Nur Juliani Ariffin, Azman Majid, Zulkepli Ismail, Muhamad Nor Akmal Shamsir, Mohd Shahir Counting in the dark: Non-intrusive laser scanning for population counting and identifying roosting bats |
title | Counting in the dark: Non-intrusive laser scanning for population counting and identifying roosting bats |
title_full | Counting in the dark: Non-intrusive laser scanning for population counting and identifying roosting bats |
title_fullStr | Counting in the dark: Non-intrusive laser scanning for population counting and identifying roosting bats |
title_full_unstemmed | Counting in the dark: Non-intrusive laser scanning for population counting and identifying roosting bats |
title_short | Counting in the dark: Non-intrusive laser scanning for population counting and identifying roosting bats |
title_sort | counting in the dark: non-intrusive laser scanning for population counting and identifying roosting bats |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3401962/ https://www.ncbi.nlm.nih.gov/pubmed/22826802 http://dx.doi.org/10.1038/srep00524 |
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