GEDI LIDAR Global Canopy Top Height Estimates for 2019 and 2020

Filtered canopy top height (RH98) estimates derived from GEDI L1B LIDAR waveforms. The data covers the globe between 51.6° north and south latitude for April through July of 2019 and 2020. Nico Lang and colleagues from ETH Zurich produced this dataset, which is associated with a 2021 publication.

Use Cases

• Training machine learning models for global canopy height regression based on LIDAR waveform data.
• Validating satellite-derived forest structure products using filtered, uncertainty-assessed height estimates.
• Analyzing seasonal (April-July) canopy height dynamics in 2019 and 2020 across vegetated land areas.
• Fusing canopy height data with optical satellite imagery (e.g., Sentinel-2) to create high-resolution models.

Strengths

• Data is filtered for predictive uncertainty and MODIS non-vegetated probability, which likely improves quality for vegetated areas.
• Covers a global spatial extent between 51.6° N and S latitude.
• Provides data for two distinct years (2019 and 2020), enabling temporal analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Temporal coverage is limited to the April-July period for the specified years.
• Row count is unknown, which may limit suitability assessment for large-scale modeling tasks.

Provenance

Source

GEDI L1B Version 1 data, processed by researchers at ETH Zurich.

Collection Method

Canopy top height (RH98) estimated from GEDI L1B waveforms and filtered based on uncertainty and land cover.

Time Range

April-July 2019 and April-July 2020

Geography

Global coverage between 51.6° N and 51.6° S latitude.