Individual tree segmentation in deciduous forests using geodesic voting

Matthew Parkan; Devis Tuia

doi:10.1109/IGARSS.2015.7325844

Individual tree segmentation in deciduous forests using geodesic voting

Matthew Parkan, Devis Tuia

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

1 Citation (Scopus)

Abstract

Airborne Laser Scanning (ALS) has been widely used to survey forest areas. The extraction (segmentation) of individual trees from ALS point clouds is a prerequisite step for tree biophysical parameter estimation. For this purpose, we develop and evaluate a graph based segmentation algorithm adapted to deciduous forests scanned with high density Li-DAR (∼50 points / m²) in leaf-off conditions. The algorithm is applied to a 1 ha deciduous forest plot in western Switzerland and the accuracy of individual trunk locations is evaluated in terms of recall, precision and F-score. The results indicate that the algorithm performs satisfactorily within the experimental setup conditions.

Original language	English
Title of host publication	2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	637-640
Number of pages	4
ISBN (Print)	9781479979295
DOIs	https://doi.org/10.1109/IGARSS.2015.7325844
Publication status	Published - 10 Nov 2015
Externally published	Yes
Event	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Milan, Italy Duration: 26 Jul 2015 → 31 Jul 2015

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2015-November

Conference

Conference	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Country	Italy
City	Milan
Period	26/07/15 → 31/07/15

Keywords

Airborne Laser Scanning
deciduous forests
geodesic voting
point clouds
Segmentation

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Parkan, M., & Tuia, D. (2015). Individual tree segmentation in deciduous forests using geodesic voting. In 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings (pp. 637-640). [7325844] (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2015-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2015.7325844

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abstract = "Airborne Laser Scanning (ALS) has been widely used to survey forest areas. The extraction (segmentation) of individual trees from ALS point clouds is a prerequisite step for tree biophysical parameter estimation. For this purpose, we develop and evaluate a graph based segmentation algorithm adapted to deciduous forests scanned with high density Li-DAR (∼50 points / m2) in leaf-off conditions. The algorithm is applied to a 1 ha deciduous forest plot in western Switzerland and the accuracy of individual trunk locations is evaluated in terms of recall, precision and F-score. The results indicate that the algorithm performs satisfactorily within the experimental setup conditions.",

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language = "English",

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Parkan, M & Tuia, D 2015, Individual tree segmentation in deciduous forests using geodesic voting. in 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings., 7325844, International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2015-November, Institute of Electrical and Electronics Engineers Inc., pp. 637-640, IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015, Milan, Italy, 26/07/15. https://doi.org/10.1109/IGARSS.2015.7325844

Individual tree segmentation in deciduous forests using geodesic voting. / Parkan, Matthew; Tuia, Devis.

2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. p. 637-640 7325844 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2015-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

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N2 - Airborne Laser Scanning (ALS) has been widely used to survey forest areas. The extraction (segmentation) of individual trees from ALS point clouds is a prerequisite step for tree biophysical parameter estimation. For this purpose, we develop and evaluate a graph based segmentation algorithm adapted to deciduous forests scanned with high density Li-DAR (∼50 points / m2) in leaf-off conditions. The algorithm is applied to a 1 ha deciduous forest plot in western Switzerland and the accuracy of individual trunk locations is evaluated in terms of recall, precision and F-score. The results indicate that the algorithm performs satisfactorily within the experimental setup conditions.

AB - Airborne Laser Scanning (ALS) has been widely used to survey forest areas. The extraction (segmentation) of individual trees from ALS point clouds is a prerequisite step for tree biophysical parameter estimation. For this purpose, we develop and evaluate a graph based segmentation algorithm adapted to deciduous forests scanned with high density Li-DAR (∼50 points / m2) in leaf-off conditions. The algorithm is applied to a 1 ha deciduous forest plot in western Switzerland and the accuracy of individual trunk locations is evaluated in terms of recall, precision and F-score. The results indicate that the algorithm performs satisfactorily within the experimental setup conditions.

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Parkan M, Tuia D. Individual tree segmentation in deciduous forests using geodesic voting. In 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2015. p. 637-640. 7325844. (International Geoscience and Remote Sensing Symposium (IGARSS)). https://doi.org/10.1109/IGARSS.2015.7325844