Introduction
Scientists report that forests are among the most effective solutions to mitigate climate change and conserve critical ecosystem services. Over the past decades, forest biomass and carbon have become essential inputs of global programs such as REDD+ that aim to mitigate climate change. Therefore, spatially continuous forest biomass maps are necessary for forest management and climate mitigation. However, there is a lack of accurate estimates of forest structure, such as forest canopy height in tropical countries.
Forest canopy height is critical for estimating above-ground biomass (AGB), carbon stock density, and forest habitat quality. Forest researchers and ecologists use forest canopy height to monitor ecosystem response to climate and land-use changes and biodiversity. Furthermore, forest canopy height is essential for assessing forest degradation and deforestation. Therefore, reliable and up-to-date information on forest canopy height and other attributes help the management of forest resources more effectively. Traditionally, forest researchers and ecologists used field measurements to collect forest canopy features. However, collecting forest canopy height information through ground measurements is time-consuming, costly, and often limited in spatial extent.
In the past decades, remote sensing researchers have used Earth observation (EO) data to map forest canopy height in forest areas. Ground, airborne and spaceborne platforms have been used to acquire oblique photographs, synthetic aperture radar (SAR), and light detection and ranging (LiDAR) or laser scanning data. Remote sensing analysts have used LiDAR to map forest canopy height. LiDAR is an active remote sensing sensor that captures the forest canopy’s three-dimensional structure. LiDAR encompasses different platforms such as terrestrial laser scanning (TLS), airborne laser scanning (ALS), drone LiDAR, and spaceborne LIDAR. While TLS and ALS provide more accurate forest canopy data, they are costly and have limited spatial and temporal coverage in large forest areas.
To overcome this critical carbon accounting gap, Earth Observation (EO) missions such as NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar instrument (Dubayah et al. 2021) onboard the International Space Station have collected vegetation structure data since April 2019. GEDI is a full waveform LIDAR designed to measure ecosystem structure and provides global coverage from 51.6° south to 51.6° north. It acquires forest vertical structure measurements in temperate and tropical forests. The LiDAR system consists of three lasers that produce eight parallel observation tracks. Each laser illuminates a 25-meter spot on the surface, where the 3D structure is measured. Every 25-meter site is separated by 60 meters along the track. There are about 600 meters between each of the eight tracks, and the system acquires data along these tracks.
To date, GEDI is used to derive several footprints and gridded products. For example, the GEDI Level 2 products contain information derived from the geolocated GEDI return waveforms. The GEDI02_A product includes ground elevation, canopy top height, and relative return energy metrics, and the GEDI02_B product provides biophysical metrics such as canopy cover and plant area index (PAI). For a detailed description of the satellite and reference data, processing schemes, approaches, methods, and other information, refer to Dubayah et al. (2021 and the GEDI mission website. This module will model forest canopy height using Google Earth Engine.