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Simulating Impacts of Ice Storms on Forest Ecosystems
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A Simulation Study Using Terrestrial LiDAR Point Cloud Data to Quantify Spectral Variability of a Broad-Leaved Forest
Renato Cifuentes1, Dimitry Van der Zande2, Christian Salas-Eljatib3,4
1Hémera Centro de Observación de la Tierra, Facultad de Ciencias, Universidad Mayor, Santiago 8340589, Chile. renato.cifuentes@gmail.com.
Sensors (Basel, Switzerland)
|October 10, 2018
Summary
Terrestrial LiDAR enables detailed forest canopy modeling. Structural changes, like leaf area density shifts, significantly impact near-infrared reflectance and vegetation indices.
Area of Science:
- Forestry
- Remote Sensing
- Geospatial Analysis
Background:
- Forest canopy structure influences spectral reflectance.
- Accurate 3D modeling is crucial for understanding canopy-radiation interactions.
Purpose of the Study:
- To assess how forest structural changes affect spectral reflectance using terrestrial LiDAR.
- To investigate the relationship between leaf area density (LAD) and canopy reflectance.
Main Methods:
- Developed a method for constructing 3D forest canopy models from terrestrial LiDAR data.
- Classified canopy elements and derived leaf area index (LAI) and LAD using a voxelized approach.
- Simulated canopy-radiation interactions in a ray tracing environment.
Main Results:
- A 10% increase in LAI had a similar effect on NIR reflectance as shifting 50% of leaf area vertically.
- Changes in canopy structure, specifically LAD, demonstrably affected vegetation indices.
- Terrestrial LiDAR proved effective for detailed canopy structural assessments.
Conclusions:
- Forest canopy structure, particularly vertical LAD, is complex and significantly impacts reflectance.
- Terrestrial LiDAR is a valuable tool for analyzing forest canopy structure and its effect on spectral properties.
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