Limitations of estimating branch volume from terrestrial laser scanning

Author:

Morhart ChristopherORCID,Schindler ZoeORCID,Frey JulianORCID,Sheppard Jonathan P.ORCID,Calders KimORCID,Disney MathiasORCID,Morsdorf FelixORCID,Raumonen PasiORCID,Seifert ThomasORCID

Abstract

AbstractQuantitative structural models (QSMs) are frequently used to simplify single tree point clouds obtained by terrestrial laser scanning (TLS). QSMs use geometric primitives to derive topological and volumetric information about trees. Previous studies have shown a high agreement between TLS and QSM total volume estimates alongside field measured data for whole trees. Although already broadly applied, the uncertainties of the combination of TLS and QSM modelling are still largely unexplored. In our study, we investigated the effect of scanning distance on length and volume estimates of branches when deriving QSMs from TLS data. We scanned ten European beech (Fagus sylvatica L.) branches with an average length of 2.6 m. The branches were scanned from distances ranging from 5 to 45 m at step intervals of 5 m from three scan positions each. Twelve close-range scans were performed as a benchmark. For each distance and branch, QSMs were derived. We found that with increasing distance, the point cloud density and the cumulative length of the reconstructed branches decreased, whereas individual volumes increased. Dependent on the QSM hyperparameters, at a scanning distance of 45 m, cumulative branch length was on average underestimated by − 75%, while branch volume was overestimated by up to + 539%. We assume that the high deviations are related to point cloud quality. As the scanning distance increases, the size of the individual laser footprints and the distances between them increase, making it more difficult to fully capture small branches and to adjust suitable QSMs.

Funder

Bundesministerium für Ernährung und Landwirtschaft

Bundesanstalt für Landwirtschaft und Ernährung

Albert-Ludwigs-Universität Freiburg im Breisgau

Publisher

Springer Science and Business Media LLC

Subject

Plant Science,Forestry

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