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

• Two structurally contrasting broadleaf forest were surveyed with ground lidar. • The wood silhouette indices are estimated using two different modeling approaches. • The absorbed PAR and NIR by leaves and wood is estimated from a ray tracing model. • Wood is found to absorb about 30–35 % of NIR energy, with implications for energy balance. Leaves in forests are commonly believed to shade many stems and branches, and thus most of the absorption of photosynthetically active radiation (PAR) within a canopy is done by leaves. Near-infrared radiation (NIR) on the other hand is not used in photosynthesis, and leaf level absorptance of NIR is much lower than it is for PAR. Still, temperate broadleaf canopies absorb about 50–70 % of incoming NIR, and how this absorption is partitioned between leaves and woody structures is unclear. Here, I show that of the NIR absorbed within the canopy space, woody structures contribute about 30–35 %. The results also confirm that leaves account for about 90 % of the absorbed PAR within the canopy space. To establish these figures, I used ground lidar measurements to map leaf area and stem and branch area in 3D in two structurally contrasting broadleaf forests, and from radiative transfer modeling I estimated the fractions of PAR and NIR absorbed by leaves and wood based on illumination conditions measured at each site over multiple years. The findings have implications for the development of land surface models that consider the storage of heat by woody biomass in forests as part of the canopy energy balance.

Authors

Institutions

Publication Details

Journal
Agricultural and Forest Meteorology
Published
2025-10-10
DOI
https://doi.org/10.1016/j.agrformet.2025.110883
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Martin Béland
Agricultural and Forest Meteorology
Remote Sensing and LiDAR Applications
article

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

Martin Béland
article en

Abstract

• Two structurally contrasting broadleaf forest were surveyed with ground lidar. • The wood silhouette indices are estimated using two different modeling approaches. • The absorbed PAR and NIR by leaves and wood is estimated from a ray tracing model. • Wood is found to absorb about 30–35 % of NIR energy, with implications for energy balance. Leaves in forests are commonly believed to shade many stems and branches, and thus most of the absorption of photosynthetically active radiation (PAR) within a canopy is done by leaves. Near-infrared radiation (NIR) on the other hand is not used in photosynthesis, and leaf level absorptance of NIR is much lower than it is for PAR. Still, temperate broadleaf canopies absorb about 50–70 % of incoming NIR, and how this absorption is partitioned between leaves and woody structures is unclear. Here, I show that of the NIR absorbed within the canopy space, woody structures contribute about 30–35 %. The results also confirm that leaves account for about 90 % of the absorbed PAR within the canopy space. To establish these figures, I used ground lidar measurements to map leaf area and stem and branch area in 3D in two structurally contrasting broadleaf forests, and from radiative transfer modeling I estimated the fractions of PAR and NIR absorbed by leaves and wood based on illumination conditions measured at each site over multiple years. The findings have implications for the development of land surface models that consider the storage of heat by woody biomass in forests as part of the canopy energy balance.

Agricultural and Forest MeteorologyVol. 375
Université Laval (CA)
Openalex Percentile: Top 74%
Remote Sensing and LiDAR Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.