Introduction
Detailed spatial information on vegetation structure, such as height, is critical for land management and planning for nature conservation, fire risk management, and greenhouse gas emissions mitigation. Traditionally, researchers used direct field measurements to collect vegetation structure parameters. However, obtaining vegetation structural parameters in the field is labor-intensive, time-consuming, and expensive and thus limited in spatial extent, typically to a few study sites. Therefore, researchers can use remote sensing methods to develop quantitative and standardized indicators of vegetation structure over broad spatial areas.
Earth observation systems such as Light Detection and Ranging (LiDAR) show potential for spatially estimating vegetation structural parameters. However, existing ground and airborne LiDAR sensors have limited spatial coverage and a relatively high acquisition cost, suitable for small local projects. Space-borne LiDAR such as GEDI provides a worldwide and broader spatial range cost-effectively. Although the GEDI measurements are sparse in both space and time, they provide critical information on ecosystem structure in temperate and tropical regions.