Béland (2025) Mapping wood area in forests from ground lidar and estimating their light interception using radiative transfer modeling

Identification

• Journal: Agricultural and Forest Meteorology
• Year: 2025
• Date: 2025-10-10
• Authors: Martin Béland
• DOI: 10.1016/j.agrformet.2025.110883

Research Groups

Digital Forest Lab, Department of Geomatics Sciences, Laval University, Quebec City, Canada

Short Summary

This study quantifies the partitioning of photosynthetically active radiation (PAR) and near-infrared radiation (NIR) absorption between leaves and woody structures in two broadleaf forests using ground lidar and radiative transfer modeling. It reveals that woody structures absorb 30–35 % of incoming NIR within the canopy space, while leaves account for approximately 90 % of absorbed PAR.

Objective

• To determine how much PAR and NIR are absorbed by leaves versus stems and branches in structurally contrasting broadleaf forests.

Study Configuration

• Spatial Scale: Two 60 m × 60 m plots in a temperate broadleaf forest (Harvard Forest EMS, USA) and a tropical rainforest (Pasoh Forest Reserve, Malaysia). Canopy heights were approximately 25 m (EMS) and 35 m (Pasoh). Canopy structure was represented using 30 cm side length voxels.
• Temporal Scale: Ground lidar data acquired in 2017 (EMS) and 2018 (Pasoh). PAR sensor measurements for validation from July 2017–2020. Radiative transfer simulations were driven by meteorological data from 1993–2020 (EMS, hourly) and 2003–2009 (Pasoh, half-hourly), focusing on July (EMS) and January (Pasoh).

Methodology and Data

• Models used:
  • Quantitative Structure Modeling (QSM) (TreeQSM) for individual tree reconstruction and wood projection G function calculation.
  • Voxel-based modeling (voxTrace) for 3D mapping of leaf area density and wood silhouette area density.
  • 3D ray tracing radiative transfer model (FLiESvox) for simulating radiation absorption.
• Data sources:
  • Ground lidar measurements (Riegl VZ-400 scanner) from 121 scan positions per site.
  • Field spectrometer measurements (NEON, 2022) for leaf optical properties.
  • Meteorological data (incoming PAR, NIR, shortwave radiation flux, diffuse fraction) from eddy covariance flux towers.
  • Ground-level PAR sensors for model validation.
  • Litter traps (EMS) and stratified clipping (Pasoh) for leaf area index (LAI) estimates.

Main Results

• Woody structures absorb 30–35 % of the total NIR energy within the canopy space (excluding ground absorption), while leaves absorb 65–70 %.
• Leaves account for approximately 90 % of the PAR absorbed within the canopy space, with woody structures absorbing about 10 %.
• Over the entire shortwave spectrum, woody structures absorb about 19 % (EMS) to 23 % (Pasoh) of the energy absorbed within the canopy space.
• Whole canopy wood silhouette area index estimates were 0.47 m²/m² (EMS) and 0.61–0.65 m²/m² (Pasoh), showing reasonable agreement between QSM and voxel-based models.
• Radiative transfer model simulations of transmitted PAR closely matched field measurements.
• The study found that characterizing the vertical variability of stem and branch angle distribution may not be necessary for simulating radiative transfer through woody structures, suggesting a constant spherical distribution (G factor of 0.5) may be appropriate.

Contributions

• Provides the first available estimates of the fraction of PAR and NIR radiation absorbed by leaves versus stems and branches within forest canopies.
• Highlights the significant role of woody structures in NIR absorption, which has implications for the canopy energy balance.
• Offers theoretical considerations for extending leaf-based statistical methods (e.g., G function) to wood area estimation, including the need to multiply the G projection factor by two for non-flat wood elements.
• Informs the development and improvement of land surface models (e.g., CLM) by providing data for better parameterization of biomass heat storage and consistent calculations of radiative forcing and available PAR for photosynthesis.

Funding

• Natural Sciences and Engineering Research Council of Canada (NSERC), funding reference numbers RGPIN-2016-06247 and ALLRP-590324-23.

Citation

@article{Béland2025Mapping,
  author = {Béland, Martin},
  title = {Mapping wood area in forests from ground lidar and estimating their light interception using radiative transfer modeling},
  journal = {Agricultural and Forest Meteorology},
  year = {2025},
  doi = {10.1016/j.agrformet.2025.110883},
  url = {https://doi.org/10.1016/j.agrformet.2025.110883}
}