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Articles by Daniel Schraik

Category: Research note

article id 10533, category Research note
Daniel Schraik, Aarne Hovi, Miina Rautiainen. (2021). Estimating cover fraction from TLS return intensity in coniferous and broadleaved tree shoots. Silva Fennica vol. 55 no. 4 article id 10533. https://doi.org/10.14214/sf.10533
Keywords: terrestrial laser scanning; leaf area; lidar intensity; physically-based; voxel
Highlights: We developed a method to obtain the fraction of TLS pulses’ footprint area covered by a target’s projection area; We tested our method with shoots of Norway spruce, Scots pine and silver birch; We provide a physically-based framework related to unmeasured variables, and provide a robust statistical framework to deal with uncertainty.
Abstract | Full text in HTML | Full text in PDF | Author Info

Terrestrial laser scanning (TLS) provides a unique opportunity to study forest canopy structure and its spatial patterns such as foliage quantity and dispersal. Using TLS point clouds for estimating leaf area density with voxel-based methods is biased by the physical dimensions of laser beams, which violates the common assumption of beams being infinitely thin. Real laser beams have a footprint size larger than several millimeters. This leads to difficulties in estimating leaf area density from light detection and ranging (LiDAR) in vegetation, where the target objects can be of similar or even smaller size than the beam footprint. To compensate for this bias, we propose a method to estimate the per-pulse cover fraction, defined as the fraction of laser beams’ footprint area that is covered by vegetation targets, using the LiDAR return intensity and an experimental calibration measurement. We applied this method to a Leica P40 single-return instrument, and report our experimental results. We found that conifer foliage had a lower average per-pulse cover fraction than broadleaved foliage, indicating an increased number of partial hits in conifer foliage. We further discuss limitations of our method that stem from unknown target properties that influence the LiDAR return intensity and highlight potential ways to overcome the limitations and manage the remaining uncertainty. Our method’s output, the per-beam cover fraction, may be useful in a weight function for methods that estimate leaf area density from LiDAR point clouds.

  • Schraik, Aalto University, School of Engineering, Department of Built Environment, P.O. Box 14100, FI-00076 Aalto, Finland; ORCID https://orcid.org/0000-0002-7794-3918 E-mail: daniel.schraik@aalto.fi (email)
  • Hovi, Aalto University, School of Engineering, Department of Built Environment, P.O. Box 14100, FI-00076 Aalto, Finland; ORCID https://orcid.org/0000-0002-4384-5279 E-mail: aarne.hovi@aalto.fi
  • Rautiainen, Aalto University, School of Engineering, Department of Built Environment, P.O. Box 14100, FI-00076 Aalto, Finland; Aalto University, School of Electrical Engineering, Department of Electronics and Nanoengineering, P.O. Box 14100, FI-00076 Aalto, Finland ORCID https://orcid.org/0000-0002-6568-3258 E-mail: miina.a.rautiainen@aalto.fi

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