Automatic Tree Annotation in LiDAR Data

Ananya Gupta, Jonathan Byrne, David Moloney, Simon Watson, Hujun Yin

2018

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.

Paper Citation

in Harvard Style

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 - Volume 1: GISTAM, ISBN 978-989-758-294-3, pages 36-41. DOI: 10.5220/0006668000360041

in Bibtex Style

@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 - Volume 1: GISTAM,},
year={2018},
pages={36-41},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006668000360041},
isbn={978-989-758-294-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - Automatic Tree Annotation in LiDAR Data
SN - 978-989-758-294-3
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