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Individual tree segmentation in deciduous forests using geodesic voting


Parkan, Matthew; Tuia, Devis (2015). Individual tree segmentation in deciduous forests using geodesic voting. In: IGARSS 2015, Milan (Italy), 26 July 2015 - 31 July 2015. IEEE, 637-640.

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 LiDAR (~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.

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 LiDAR (~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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Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Physical Sciences > Computer Science Applications
Physical Sciences > General Earth and Planetary Sciences
Language:English
Event End Date:31 July 2015
Deposited On:14 Jan 2016 09:00
Last Modified:26 Oct 2021 11:10
Publisher:IEEE
ISBN:978-1-4799-7929-5
OA Status:Closed
Free access at:Official URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1109/IGARSS.2015.7325844
Official URL:http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7325844

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