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LeafGen: Leaf generation in 3D tree models

Mönkkönen, Pietari; Van den Broeck, Wouter; Ali-Löytty, Simo; Calders, Kim; Raumonen, Pasi (2025-08)

 
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Methods_Ecol_Evol_-_2025_-_M_nkk_nen_-_LeafGen_Leaf_generation_in_3D_tree_models.pdf (6.846Mt)
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Mönkkönen, Pietari
Van den Broeck, Wouter
Ali-Löytty, Simo
Calders, Kim
Raumonen, Pasi
08 / 2025

Methods in Ecology and Evolution
doi:10.1111/2041-210X.70080
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202507237742

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Peer reviewed
Tiivistelmä
Leaves are crucial for tree growth, survival and interaction with the environment. The spatial arrangement of leaves within the tree canopy significantly influences tree-environment interactions, such as sunlight capture, scattering and shading, as well as rainfall interception. The impact of leaf configurations on ecological processes can be studied using virtual 3D foliage models. These models are valuable for ecological simulations and modelling applications, as well as for the development and validation of remote sensing methods. This virtual approach enables the study of leaf attributes and interactions in a controlled, reproducible and cost-effective manner. The study introduces LeafGen, a new MATLAB-based foliage generation method to generate explicit leaves on 3D tree models. The leaf cover is generated based on user-defined leaf area density, orientation, and size distributions with flexible and configurable distribution types and parameters. The foliage can be generated either on cylinder-based 3D tree models (quantitative structure models) or point clouds of trees. The distributions are defined on structural variables of the tree models, making the definition straightforward and simple but allowing diverse configurations. Species-specific traits can also be incorporated with specific leaf geometries and phyllotaxis patterns. The leaves are generated without intersections to ensure realistic foliage. LeafGen provides an easily accessible and low-entry tool for ecological research, enabling precise control over leaf attributes and their distribution. The method is open source and has a publicly hosted repository on GitHub along with guidance on implementing different scenarios. This method enhances the reproducibility and cost-effectiveness of studies on leaf–environment interactions and can be applied to various applications, including forest remote sensing, light transfer modelling and tree growth simulations.
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  • TUNICRIS-julkaisut [23847]
Kalevantie 5
PL 617
33014 Tampereen yliopisto
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Kalevantie 5
PL 617
33014 Tampereen yliopisto
oa[@]tuni.fi | Tietosuoja | Saavutettavuusseloste