Automatic bat counting and identification of bat species using terrestrial laser scanning

The current practice in roosting bat population survey and species identification is either based on net capture, visual observation or optical-mechanical count methods. However, these methods are intrusive, tedious, time consuming and at best, only reports an estimation of the roosting population o...

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Main Author:	Noor Azmy, Suzanna
Format:	Thesis
Language:	English
Published:	2013
Subjects:	QL Zoology
Online Access:	http://eprints.utm.my/id/eprint/36722/5/SuzannaNoorAzmyMFBSK2013.pdf
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id	my-utm-ep.36722
record_format	uketd_dc
spelling	my-utm-ep.367222017-06-29T07:10:25Z Automatic bat counting and identification of bat species using terrestrial laser scanning 2013-08 Noor Azmy, Suzanna QL Zoology The current practice in roosting bat population survey and species identification is either based on net capture, visual observation or optical-mechanical count methods. However, these methods are intrusive, tedious, time consuming and at best, only reports an estimation of the roosting population of bats. Here, the present study showed the use of Light Detection and Ranging (LIDAR) concept using terrestrial laser scanner was successful in remotely identifying and determining the exact population of roosting bats in caves. The laser scans accurately captured the three dimensional (3D) features of the roosting bats and their spatial distribution pattern in total darkness. Using LIDAR, the determination number of bats can be conducted, spatially analyze the 3D distribution of bat populations as well as generate a 3D topological structure of the roosting cave. This resulted in a high resolution model of the cave, enabling exact count of visibly differentiated individual bats. This successfully leads to the species identification of the Hipposideros larvatus and Hipposideros armiger reported in this study. This studies anticipate that the development of the LIDAR into a non-intrusive technique will open up new possibilities in bat roosting studies. This novel method would possibly allow future works accomplishment of researchers to study roosting behavior such as maternity roosting patterns, roost sharing and roost-switching patterns within the topographical context of the speleological (caves, subterranean spaces and caverns) internal surface, thus making rigorous quantitative characterizations of cave roosting behavior possible. The final results of this study would be an automated procedure for bat population count and the function of point cloud data in assisting the species identification. 2013-08 Thesis http://eprints.utm.my/id/eprint/36722/ http://eprints.utm.my/id/eprint/36722/5/SuzannaNoorAzmyMFBSK2013.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Biosciences and Medical Engineering Faculty of Biosciences and Medical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QL Zoology
spellingShingle	QL Zoology Noor Azmy, Suzanna Automatic bat counting and identification of bat species using terrestrial laser scanning
description	The current practice in roosting bat population survey and species identification is either based on net capture, visual observation or optical-mechanical count methods. However, these methods are intrusive, tedious, time consuming and at best, only reports an estimation of the roosting population of bats. Here, the present study showed the use of Light Detection and Ranging (LIDAR) concept using terrestrial laser scanner was successful in remotely identifying and determining the exact population of roosting bats in caves. The laser scans accurately captured the three dimensional (3D) features of the roosting bats and their spatial distribution pattern in total darkness. Using LIDAR, the determination number of bats can be conducted, spatially analyze the 3D distribution of bat populations as well as generate a 3D topological structure of the roosting cave. This resulted in a high resolution model of the cave, enabling exact count of visibly differentiated individual bats. This successfully leads to the species identification of the Hipposideros larvatus and Hipposideros armiger reported in this study. This studies anticipate that the development of the LIDAR into a non-intrusive technique will open up new possibilities in bat roosting studies. This novel method would possibly allow future works accomplishment of researchers to study roosting behavior such as maternity roosting patterns, roost sharing and roost-switching patterns within the topographical context of the speleological (caves, subterranean spaces and caverns) internal surface, thus making rigorous quantitative characterizations of cave roosting behavior possible. The final results of this study would be an automated procedure for bat population count and the function of point cloud data in assisting the species identification.
format	Thesis
qualification_level	Master's degree
author	Noor Azmy, Suzanna
author_facet	Noor Azmy, Suzanna
author_sort	Noor Azmy, Suzanna
title	Automatic bat counting and identification of bat species using terrestrial laser scanning
title_short	Automatic bat counting and identification of bat species using terrestrial laser scanning
title_full	Automatic bat counting and identification of bat species using terrestrial laser scanning
title_fullStr	Automatic bat counting and identification of bat species using terrestrial laser scanning
title_full_unstemmed	Automatic bat counting and identification of bat species using terrestrial laser scanning
title_sort	automatic bat counting and identification of bat species using terrestrial laser scanning
granting_institution	Universiti Teknologi Malaysia, Faculty of Biosciences and Medical Engineering
granting_department	Faculty of Biosciences and Medical Engineering
publishDate	2013
url	http://eprints.utm.my/id/eprint/36722/5/SuzannaNoorAzmyMFBSK2013.pdf
_version_	1747816449951399936

Automatic bat counting and identification of bat species using terrestrial laser scanning

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