3D lidar imaging for detecting and understanding plant responses and canopy structure

Area of Science:

• Plant science
• Remote sensing
• Ecology

Background:

• Plant stress responses are intrinsically linked to their three-dimensional (3D) structures.
• Accurate measurement of plant properties is crucial for understanding stress impacts.
• Traditional methods often lack the resolution to capture complex 3D plant architecture.

Purpose of the Study:

• To demonstrate the utility of 3D light detection and ranging (lidar) imaging for plant property estimation.
• To review the application of lidar systems in assessing plant growth and shape responses to stress.
• To explore the integration of lidar data with other imaging techniques for comprehensive plant stress analysis.

Main Methods:

• Utilizing 3D lidar imaging for direct measurement of plant structure.
• Estimating plant properties like canopy height, structure, carbon stock, and species identification.
• Combining lidar data with natural color, chlorophyll fluorescence, and thermal imaging.
• Integrating multi-modal imaging data using computer graphics techniques.

Main Results:

• Lidar effectively estimates key plant properties and assesses growth and shape responses.
• Integrated imaging provides insights into pigment, photosynthesis, and transpiration responses to stress.
• 3D lidar data combined with other sensors offer a holistic view of plant ecophysiological status.

Conclusions:

• 3D lidar imaging is a powerful tool for understanding plant responses to environmental stress.
• Future lidar advancements will enhance dynamic estimation of plant properties and environmental interactions.
• Combining lidar with other imaging techniques will improve remote sensing accuracy for ecological and agricultural applications.