Lidar Remote Sensing of Forest Canopy Structure
Summary
Lidar (Light Detection and Ranging) employs airborne or spaceborne laser pulses to quantify vertical forest structure with unprecedented precision. By recording the time delay and intensity of returned signals, it generates three-dimensional point clouds that capture canopy height, density and foliage distribution. This permits estimation of aboveground biomass, gap dynamics and carbon stocks at scales ranging from individual trees to entire biomes. Advances in sensor design and waveform analysis have enhanced penetration beneath the canopy surface, enabling retrieval of understory structure and ground elevation. Integration with optical imagery, radar data and machine-learning models has extended coverage to regions where airborne campaigns are infeasible, supporting global monitoring of forest health, biodiversity and responses to climatic disturbances.
Research from Nature Portfolio
Systematic analysis of LiDAR waveforms over the Amazon basin revealed lasting reductions in canopy height and carbon density following the 2005 mega-drought. Persistent declines in average LiDAR-derived forest height corresponded to annual losses of aboveground biomass carbon, demonstrating that severe drought events can induce multi-year feedbacks on forest carbon sinks. This foundational work underscores the sensitivity of large tropical forests to climatic extremes and validates LiDAR as a tool for tracking disturbance impacts across continental scales.
Lidar Remote Sensing of Forest Canopy Structure publication trend
The graph below shows the total number of articles in lidar remote sensing of forest canopy structure across all publications each year (not limited to Nature Index journals).
Technical terms
LiDAR: A remote-sensing technique that emits laser pulses and measures return time to map three-dimensional structures.
Point Cloud: A dense collection of spatial coordinates representing the surfaces encountered by LiDAR pulses.
Waveform: The full profile of laser energy as a function of time, indicating canopy layers and ground returns.
Canopy Height Model (CHM): A raster representation of the vertical distance between the ground surface and the top of the vegetation canopy.
GEDI: Global Ecosystem Dynamics Investigation, a spaceborne LiDAR mission designed for detailed forest structure mapping.
Aboveground Biomass Carbon Density (ACD): The mass of carbon stored per unit area in living vegetation above the soil surface, derived from structural metrics.
References
- Canopy Height Mapping for Plantations in Nigeria Using GEDI, Landsat, and Sentinel-2. Remote Sensing (2023).
- Post-drought decline of the Amazon carbon sink. Nature Communications (2018).
- Modelling forest canopy height by integrating airborne LiDAR samples with satellite Radar and multispectral imagery. International Journal of Applied Earth Observation and Geoinformation (2018).
About these summaries
This Nature Research Intelligence Topic summary is created with the cited references and a large language model. We take care to ground generated text with facts, and have systems in place to gain human feedback on the overall quality of the process in line with our AI principles. We strive to create accurate and useful summaries for people unfamiliar with the research topic and that supports this goal. These pages are a beta release and will be updated as we learn how best to help people gain value from a research topic summary.
Turn complex research questions into confident strategic decisions
When you're under pressure to set direction, justify investment, or understand your competitive position, you need more than raw data — you need trusted insights you can act on.
Benchmark your performance against global peers using robust, methodologically sound analysis.
Combine quantitative metrics with qualitative expert insight to uncover strengths, gaps and emerging opportunities.
Gain tailored, decision-ready recommendations aligned to your strategic priorities.
Talk to us to learn more about our data dashboards and bespoke strategy reports.
Grow research skills, confidence and careers with training built for every stage of the research lifecycle.
Developed with Nature Portfolio journal Editors and internationally renowned experts. Discover three ways to learn:
Self-paced, online courses in convenient bite-sized units, covering key skills across scientific writing, publishing, grant writing, data analysis, and more.
Expert trainer-led workshops with hands-on exercises and real-time feedback across core research skills, delivered via interactive group sessions.
Editor-led workshops combining core principles in writing and publishing, personalised 1:1 feedback from Nature Portfolio Editors and hands-on exercises.
Explore course catalogues and workshop agendas, enquire about the options or request institutional pricing.