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Articles by Pasi Raumonen

Category : Research article

article id 10550, category Research article
Miro Demol, Phil Wilkes, Pasi Raumonen, Sruthi M. Krishna Moorthy, Kim Calders, Bert Gielen, Hans Verbeeck. (2022). Volumetric overestimation of small branches in 3D reconstructions of Fraxinus excelsior. Silva Fennica vol. 56 no. 1 article id 10550. https://doi.org/10.14214/sf.10550
Keywords: aboveground biomass; crown architecture; LIDAR; quantitative structure models; common ash; woody tree volume
Highlights: We compare branch diameter and tree woody volume estimates from terrestrial laser scanning data with manual measurements of two Fraxinus excelsior trees; Smaller branch diameters are generally overestimated due to scattering and misalignment errors in the point cloud; Consequently, tree woody volume is overestimated by 38% to 52%; Filtering by reflectance and improved alignment partly mitigate this effect.
Abstract | Full text in HTML | Full text in PDF | Author Info

Terrestrial laser scanning (TLS) has been applied to estimate forest wood volume based on detailed 3D tree reconstructions from point cloud data. However, sources of uncertainties in the point cloud data (alignment and scattering errors, occlusion, foliage...) and the reconstruction algorithm type and parameterisation are known to affect the reconstruction, especially around finer branches. To better understand the impacts of these uncertainties on the accuracy of TLS-derived woody volume, high-quality TLS scans were collected in leaf-off conditions prior to destructive harvesting of two forest-grown common ash trees (Fraxinus excelsior L.; diameter at breast height ~28 cm, woody volume of 732 and 868 L). We manually measured branch diameters at 265 locations in these trees. Estimates of branch diameters and tree volume from Quantitative Structure Models (QSM) were compared with these manual measurements. The accuracy of QSM branch diameter estimates decreased with smaller branch diameters. Tree woody volume was overestimated (+336 L and +392 L) in both trees. Branches measuring < 5 cm in diameter accounted for 80% and 83% of this overestimation respectively. Filtering for scattering errors or improved coregistration approximately halved the overestimation. Range filtering and modified scanning layouts had mixed effects. The small branch overestimations originated primarily in limitations in scanner characteristics and coregistration errors rather than suboptimal QSM parameterisation. For TLS-derived estimates of tree volume, a higher quality point cloud allows smaller branches to be accurately reconstructed. Additional experiments need to elucidate if these results can be generalised beyond the setup of this study.

  • Demol, CAVElab – Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium; PLECO – Plants and Ecosystems, Faculty of Science, Antwerp University, Universiteitsplein 1, B-2610 Wilrijk, Belgium ORCID https://orcid.org/0000-0002-5492-2874 E-mail: miro.demol@ugent.be (email)
  • Wilkes, UCL Department of Geography, Gower Street, London WC1E 6BT, UK; NERC National Centre for Earth Observation (NCEO), UK ORCID https://orcid.org/0000-0001-6048-536X E-mail: p.wilkes@ucl.ac.uk
  • Raumonen, Mathematics, Tampere University, FI-33101 Tampere, Finland ORCID https://orcid.org/0000-0001-5471-0970 E-mail: pasi.raumonen@tuni.fi
  • Krishna Moorthy, CAVElab – Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium ORCID https://orcid.org/0000-0002-6838-2880 E-mail: Sruthi.KrishnaMoorthyParvathi@ugent.be
  • Calders, CAVElab – Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium ORCID https://orcid.org/0000-0002-4562-2538 E-mail: kim.calders@ugent.be
  • Gielen, PLECO – Plants and Ecosystems, Faculty of Science, Antwerp University, Universiteitsplein 1, B-2610 Wilrijk, Belgium ORCID https://orcid.org/0000-0002-4890-3060 E-mail: bert.gielen@uantwerpen.be
  • Verbeeck, CAVElab – Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium ORCID https://orcid.org/0000-0003-1490-0168 E-mail: hans.verbeeck@ugent.be
article id 1413, category Research article
Ilya Potapov, Marko Järvenpää, Markku Åkerblom, Pasi Raumonen, Mikko Kaasalainen. (2015). Data-based stochastic modeling of tree growth and structure formation. Silva Fennica vol. 50 no. 1 article id 1413. https://doi.org/10.14214/sf.1413
Keywords: terrestrial lidar; form diversity; morphological plasticity; stochastic functional-structural plant model; quantitative structure models; data fitting
Highlights: We propose a stochastic version of the tree growth model LIGNUM for producing tree structures consistent with detailed terrestrial laser scanning data, and we provide the proof-of-concept by using model-based simulations and real laser scanning data; Trees produced with the data-based model resemble the trees of the dataset, and are statistically similar but not copies of each other; the number of such synthetic trees is not limited.
Abstract | Full text in HTML | Full text in PDF | Author Info

We introduce a general procedure to match a stochastic functional-structural tree model (here LIGNUM augmented with stochastic rules) with real tree structures depicted by quantitative structure models (QSMs) based on terrestrial laser scanning. The matching is done by iteratively finding the maximum correspondence between the measured tree structure and the stochastic choices of the algorithm. First, we analyze the match to synthetic data (generated by the model itself), where the target values of the parameters to be estimated are known in advance, and show that the algorithm converges properly. We then carry out the procedure on real data obtaining a realistic model. We thus conclude that the proposed stochastic structure model (SSM) approach is a viable solution for formulating realistic plant models based on data and accounting for the stochastic influences.

  • Potapov, Tampere University of Technology, Department of Mathematics, P.O. Box 553, FI-33101 Tampere, Finland E-mail: ilya.potapov@tut.fi (email)
  • Järvenpää, Tampere University of Technology, Department of Mathematics, P.O. Box 553, FI-33101 Tampere, Finland E-mail: marko.jarvenpaa@tut.fi
  • Åkerblom, Tampere University of Technology, Department of Mathematics, P.O. Box 553, FI-33101 Tampere, Finland E-mail: markku.akerblom@tut.fi
  • Raumonen, Tampere University of Technology, Department of Mathematics, P.O. Box 553, FI-33101 Tampere, Finland E-mail: pasi.raumonen@tut.fi
  • Kaasalainen, Tampere University of Technology, Department of Mathematics, P.O. Box 553, FI-33101 Tampere, Finland E-mail: mikko.kaasalainen@tut.fi

Category : Research note

article id 1125, category Research note
Anssi Krooks, Sanna Kaasalainen, Ville Kankare, Marianna Joensuu, Pasi Raumonen, Mikko Kaasalainen. (2014). Predicting tree structure from tree height using terrestrial laser scanning and quantitative structure models. Silva Fennica vol. 48 no. 2 article id 1125. https://doi.org/10.14214/sf.1125
Keywords: remote sensing; terrestrial lidar; tree modelling; branch size distribution
Highlights: The analysis of tree structure suggests that trees of different height growing in similar conditions have similar branch size distributions; There is potential for using the tree height information in large-scale estimations of forest canopy structure.
Abstract | Full text in HTML | Full text in PDF | Author Info
We apply quantitative structure modelling to produce detailed information on branch-level metrics in trees. Particularly we are interested in the branch size distribution, by which we mean the total volume of branch parts distributed over the diameter classes of the parts. We investigate the possibility of predicting tree branch size distributions for trees in similar growing conditions. The quantitative structure model enables for the first time the comparisons of structure between a large number of trees. We found that the branch size distribution is similar for trees of different height in similar growing conditions. The results suggest that tree height could be used to estimate branch size distribution in areas with similar growing conditions and topography.
  • Krooks, Finnish Geodetic Institute, Geodeetinrinne 2, FI–02431 Masala, Finland E-mail: Anssi.Krooks@fgi.fi
  • Kaasalainen, Finnish Geodetic Institute, Geodeetinrinne 2, FI–02431 Masala, Finland E-mail: Sanna.Kaasalainen@fgi.fi (email)
  • Kankare, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 Helsinki, Finland E-mail: ville.kankare@helsinki.fi
  • Joensuu, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 Helsinki, Finland E-mail: marianna.joensuu@alumni.helsinki.fi
  • Raumonen, Tampere University of Technology, Department of Mathematics, P.O. Box 553, Tampere, FI-33101, Finland E-mail: Pasi.Raumonen@tut.fi
  • Kaasalainen, Tampere University of Technology, Department of Mathematics, P.O. Box 553, Tampere, FI-33101, Finland E-mail: Mikko.Kaasalainen@tut.fi

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