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Gewählte Publikation:

Ritter, T; Schwarz, M; Tockner, A; Leisch, F; Nothdurft, A.
(2017): Automatic Mapping of Forest Stands Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning
FORESTS. 2017; 8(8): FullText FullText_BOKU

Abstract:
Mapping of exact tree positions can be regarded as a crucial task of field work associated with forest monitoring, especially on intensive research plots. We propose a two-stage density clustering approach for the automatic mapping of tree positions, and an algorithm for automatic tree diameter estimates based on terrestrial laser-scanning (TLS) point cloud data sampled under limited sighting conditions. We show that our novel approach is able to detect tree positions in a mixed and vertically structured stand with an overall accuracy of 91.6%, and with omission-and commission error of only 5.7% and 2.7% respectively. Moreover, we were able to reproduce the standxxxs diameter in breast height (DBH) distribution, and to estimate single trees DBH with a mean average deviation of +/- 2.90 cm compared with tape measurements as reference.
Autor/innen der BOKU Wien:
Leisch Friedrich
Nothdurft Arne
Ritter Tim
Schwarz Marcel
Tockner Andreas
BOKU Gendermonitor:


Find related publications in this database (Keywords)
terrestrial laser scanning
forest inventory
density-based clustering


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