Related Experiment Video
Updated: Jun 24, 2025
00:09
Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands
Published on: August 29, 2019
13.5K
3-dimensional surface geometry dataset of Scots pine and Norway spruce shoots from the Järvselja RAdiation transfer
Jan Pisek1, Oleksandr Borysenko1,2
1University of Tartu, Tartu Observatory, Observatooriumi 1, 61602 Tõravere, Tartumaa, Estonia.
Data in Brief
|June 13, 2024
Summary
This study introduces a new 3D dataset of conifer shoots, including Scots pine and Norway spruce. These detailed scans improve radiative transfer models for more accurate forest simulations.
Area of Science:
- Forestry and Remote Sensing
- Computational Geometry
- Radiative Transfer Physics
Background:
- Accurate radiative transfer models require detailed 3D representations of forest canopies.
- Previous models of conifer shoots were too coarse for precise radiation scattering analysis.
- Understanding conifer shoot geometry is crucial for ecosystem process modeling.
Purpose of the Study:
- To present a high-resolution 3D dataset of conifer shoots for improved radiative transfer modeling.
- To provide realistic 3D surface reconstructions of Scots pine and Norway spruce shoots.
- To facilitate more accurate simulations of radiation scattering in conifer stands.
Main Methods:
- Collected 3D surface data of 10 conifer shoots (5 Scots pine, 5 Norway spruce) in Estonia.
- Utilized blue light 3D photogrammetry scanning for high-resolution point cloud generation.
- Acquired detailed 3D surface reconstructions and photographic data for each sampled shoot.
Main Results:
- Generated a dataset of 3D point clouds for individual Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) shoots.
- The dataset captures intricate spatial details of conifer shoot geometry.
- Provides realistic digital representations to replace artificial models.
Conclusions:
- The new 3D conifer shoot dataset enhances the realism of 3D forest representations.
- Enables more accurate parameter and process estimations in radiative transfer models.
- Contributes to improved understanding of light-matter interactions in forest ecosystems.
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