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Authors: Ananya Gupta 1 ; Jonathan Byrne 2 ; David Moloney 2 ; Simon Watson 3 and Hujun Yin 3

Affiliations: 1 The University of Manchester and Intel Corporation, United Kingdom ; 2 Intel Corporation, Ireland ; 3 The University of Manchester, United Kingdom

Keyword(s): Airborne LiDAR, Urban Areas, Classification, Tree Detection, Voxelization.

Abstract: LiDAR provides highly accurate 3D point cloud data for a number of tasks such as forest surveying and urban planning. Automatic classification of this data, however, is challenging since the dataset can be extremely large and manual annotation is labour intensive if not impossible. We provide a method of automatically annotating airborne LiDAR data for individual trees or tree regions by filtering out the ground measurements and then using the number of returns embedded in the dataset. The method is validated on a manually annotated dataset for Dublin city with promising results.

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Paper citation in several formats:
Gupta, A.; Byrne, J.; Moloney, D.; Watson, S. and Yin, H. (2018). Automatic Tree Annotation in LiDAR Data. In Proceedings of the 4th International Conference on Geographical Information Systems Theory, Applications and Management - GISTAM; ISBN 978-989-758-294-3; ISSN 2184-500X, SciTePress, pages 36-41. DOI: 10.5220/0006668000360041

@conference{gistam18,
author={Ananya Gupta. and Jonathan Byrne. and David Moloney. and Simon Watson. and Hujun Yin.},
title={Automatic Tree Annotation in LiDAR Data},
booktitle={Proceedings of the 4th International Conference on Geographical Information Systems Theory, Applications and Management - GISTAM},
year={2018},
pages={36-41},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006668000360041},
isbn={978-989-758-294-3},
issn={2184-500X},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Geographical Information Systems Theory, Applications and Management - GISTAM
TI - Automatic Tree Annotation in LiDAR Data
SN - 978-989-758-294-3
IS - 2184-500X
AU - Gupta, A.
AU - Byrne, J.
AU - Moloney, D.
AU - Watson, S.
AU - Yin, H.
PY - 2018
SP - 36
EP - 41
DO - 10.5220/0006668000360041
PB - SciTePress