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Forests 2017, 8(8), 265; doi:10.3390/f8080265

Automatic Mapping of Forest Stands Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning

1
Department of Forest- and Soil Science, Institute of Forest Growth, University of Natural Resources and Life Sciences (BOKU), Vienna 1180, Austria
2
Department of Landscape, Spatial and Infrastructure Sciences, Institute of Applied Statistics and Computing, University of Natural Resources and Life Sciences (BOKU), Vienna 1180, Austria
*
Author to whom correspondence should be addressed.
Received: 6 July 2017 / Revised: 20 July 2017 / Accepted: 21 July 2017 / Published: 25 July 2017
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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 stand’s 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. View Full-Text
Keywords: terrestrial laser scanning; forest inventory; density-based clustering terrestrial laser scanning; forest inventory; density-based clustering
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Ritter, T.; Schwarz, M.; Tockner, A.; Leisch, F.; Nothdurft, A. Automatic Mapping of Forest Stands Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning. Forests 2017, 8, 265.

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