Why GEDI? Mission Objectives and Global Relevance
In this section:
- Learn about the GEDI mission’s purpose and technology specifications.
- Quick overview of available data products, where they are located and what they represent.
- Introduction to GEDI’s application areas.
Watch this video on the GEDI instrument Source: NASA Scientific Visualization Studio (2018).
The GEDI Mission
The Global Ecosystem Dynamics Investigation (GEDI) produces high resolution laser ranging observations of Earth’s 3-dimensional surface structures. GEDI’s precise measurements of forest canopy height, canopy vertical structure, and surface elevation advance society’s ability to understand important atmospheric and water cycling processes, biodiversity, and habitat (GEDI webpage). The mission is led by the University of Maryland in collaboration with NASA Goddard Space Flight Center. GEDI’s scientific data and algorithms are created by the GEDI Science Definition Team from across programs to respond to several fundamental global challenges.
The mission objectives:
Source: GEDI Mission.
GEDI is a “geodetic-class,” light detection and ranging (lidar) laser system. Three lasers that produce eight parallel ground tracks each fire 242 times per second to illuminate a 25m footprint over the surface where the vertical structure is measured. There are about 600m between each of the eight ground tracks, where each footprint is sampled 60m apart along the track. Tens of billions of cloud-free observations have been collected. Since GEDI is a sensor aboard the International Space Station (ISS), it follows the station’s orbital path, and collects observations between 51.6° N & S latitude. The mission collected data from April 4, 2019 - March 16, 2023. A period of hibernation when no data was collected ensued from March 16, 2023 - April 26, 2024. It has resumed activity since then, and is set to continue until ~2030.
Source: GEDI Mission.
GEDI is unique since it is the first of its kind-a space-based lidar optimized to retrieve vegetation vertical structure. Such a feat was accomplished by over 20 years of spaceborne laser altimetry and terrestrial ecology community advancements in lidar.
Source: The GEDI Mission - Calibration and Validation
Other lidar or field based means of collecting vegetation height, canopy cover, plant area, plant area volume density, or foliage height diversity have various trade-offs regarding geographical coverage, spatial and temporal resolution, and density or ease of access and analysis:
- Field plots are the most accurate given they are representative of on-site (in situ) observations done by professional interpretation. While the plots may be well documented, the plot shape, size, date of observation, and public access limitations could prove challenging when trying to find these high value plots that overlap with lidar observations.
- Terrestrial lidar systems (TLS) have incredibly high spatial resolution and data density collecting structural information on site, usually as a 360 view of the forest. The sites can be quite small, and require heavy data storage, costly equipment, and specialized skill to process.
- Unmanned airborne vehicles (UAV) can widen the spatial coverage, still at relatively high resolutions compared to airborne and terrestrial lidar, and do not require as much physical trekking and optimized ground placement and positioning as terrestrial lidar systems do, nor do they require an on flight team like airborne campaigns.
- Airborne lidar systems (ALS) provide comprehensive and high resolution observations across larger areas than UAV or terrestrial lidar. GEDI’s design, calibration, and validation are largely built from years of research with airborne lidar systems, such as LVIS (Land, Vegetation and Ice Sensor (Blair et al., 1999)).
- For each of the related data collection methods: field plot, terrestrial, UAV or airborne sensors, getting collection campaigns to be funded and planned frequently can be expensive and time consuming. Space-based lidar like GEDI and the ICESats, are freely available and more frequently collected datasets by comparison, with tradeoffs to resolution and precise continuous return observations.
Spaceborne lidar by comparison proves to be a great technical feat in achieving lidar observations from space with trade-offs in spatial resolution and sampling density. Comparatively, space-based lidar has greatly increased the number of observations globally over time, though precise repeat and consistent high-quality observations are still a challenge. GEDI builds upon earlier spaceborne lidar missions like ICESat (Geoscience Laser Altimeter System - GLAS). However, ICESat had a larger footprint size, which could introduce substantial measurement uncertainty of canopy structure, especially over steep slopes. GEDI’s smaller 25m footprint provides alternative higher resolution and unique sampling patterns. For example, after 3 months, GEDI accumulated almost 200 million observations over pantropical land areas, compared to ~3-5 million shots for pan-tropical biomass maps based on ICESat. The follow-on to ICESat, which is ICESat-2, has shown significant similar contribution to global lidar based elevation and height metrics as GEDI. Combined GEDI with ICESat-2 datasets have demonstrated improved overall space-based lidar estimations, making for a promising step towards building upon accurate structural estimates across decades of existing data and adapting to future continuous lidar missions.
Global Ecosystem Dynamics Investigation Spaceborne Lidar Quick Look Products
View the GEDI Data Product Reference Tables
A reference table for GEDI data product levels 1-4 and several derived products and their homepages are listed here for access to documentation, NASA access and visualization tools, and other resources.
*Temporal extent may be updated by version number, or specific datasets within the product may reflect different dates.
| Data Products | Resolution | Spatial Coverage | *Temporal Extent | Temporal Resolution | Algorithm Theoretical Based Document (ATBD) | Archive / Data Dictionary | Data Format |
|---|---|---|---|---|---|---|---|
| GEDI01_A-TX Transmitted Waveform Fitted Parameters & GEDI01_A-RX Received Waveform Fitted Parameters | 25 m (~82 ft) diameter | N: 54, S: -54, E: 180, W: -180 | 2019-04-04 to 2023-03-16 & 2024-04-26 to Present | Varies | L1A-2A: Transmit and Receive Waveform Interpretation and Generation of L1A and L2A products | Not publicly available | HDF5 |
| GEDI01_B: Footprint Level Geolocated Waveform Data | 25 m (~82 ft) diameter | N: 54, S: -54, E: 180, W: -180 | 2019-04-04 to 2023-03-16 & 2024-04-26 to Present | Varies | L1B: Waveform Geolocation for L1 and L2 Products | LP DAAC | HDF5 |
| GEDI02_A: Footprint Level Elevation and Height Metrics – Ground elevation, canopy top height, relative height (RH) metrics. | 25 m (~82 ft) diameter | N: 54, S: -54, E: 180, W: -180 | 2019-04-04 to 2023-03-16 & 2024-04-26 to Present | Varies | L1A-2A: Transmit and Receive Waveform Interpretation and Generation of L1A and L2A products | LP DAAC | HDF5 |
| GEDI02_B: Footprint Level Canopy Cover and Vertical Profile Metrics – Canopy Cover Fraction (CCF), CCF profile, Plant Area Index (PAI), PAI profile, Plant Area Volume Density (PAVD) profile, Foliage Height Diversity (FHD). | 25 m (~82 ft) diameter | N: 54, S: -54, E: 180, W: -180 | 2019-04-04 to 2023-03-16 & 2024-04-26 to Present | Varies | L2B: Footprint Canopy Cover and Vertical Profile Metrics | LP DAAC | HDF5 |
| GEDI03: Gridded Level 2 Land Surface metrics – Mean and standard deviation of RH100 and ground elevation, counts of laser footprints within each grid. | 1 km (~0.6 mi) grids | N: 52, S: -52, E: 180, W: -180 | 2019-04-18 to 2023-03-22 | Varies | L3: Gridded Land Surface Metrics | ORNL DAAC | GeoTIFF |
| GEDI04_A: Footprint Level Above Ground Biomass Density (AGBD) | 25 m (~82 ft) diameter | N: 55.8, S: -53, E: 180, W: -180 | 2019-04-17 to 2025-03-19 | Varies | L4A: Footprint Above Ground Biomass Density | ORNL DAAC | HDF5 |
| GEDI04_B: Gridded Above Ground Biomass Density (AGBD) | 1 km (~0.6 mi) grids | N: 52, S: -52, E: 180, W: -180 | 2019-04-18 to 2023-03-16 | Varies | L4B: Gridded Biomass Product | ORNL DAAC | GeoTIFF |
| GEDI04_C: Footprint Level Waveform Structural Complexity Index | 25 m (~82 ft) diameter | N: 55.8, S: -53, E: 180, W: -180 | 2019-04-17 to 2025-03-19 | Varies | L4C: Footprint waveform structural complexity index | ORNL DAAC | HDF5 |
| Derived Product: Level 4B Country-level Summaries of Above Ground Biomass | Country level | N: 52, S: -52, E: 180, W: -180 | 2019-04-18 to 2023-03-16 | Varies | Country estimates of mean above ground biomass density and total above ground biomass stocks | ORNL DAAC | GeoTIFF |
| Derived Product: Pantropical Forest Height and Biomass from GEDI and TanDEM-X Data Fusion | 25 m, 100 m | Mexico, Gabon, French Guiana, Amazonia | 2011-01-06 to 2021-08-18 | Varies | Mapping large-scale pantropical forest canopy height by integrating GEDI lidar and TamDEM-X InSAR data | ORNL DAAC | GeoTIFF |
| Derived Product: Global Vegetation Height Metrics from GEDI and ICESat-2 | 100 m, 200 m, 500 m, 1000 m | N: 90, S: -90, E: 180, W: -180 | 2019-01-01 to 2022-12-31 | Varies | ORNL DAAC | GeoTIFF | |
| Derived Product: Gridded GEDI Vegetation Structure Metrics and Biomass Density at Multiple Resolutions | 1 km, 6 km, and 12 km grids | N: 52.2, S: -52.2, E: 180, W: -180 | 2019-04-17 to 2023-03-16 | Varies | ORNL DAAC | GeoTIFF |
How do I access the data?
GEDI L1-2 are maintained by LP DAAC, and all other data by the ORNL DAAC. The EarthData catalog is where all products and documentation are stored.
Where can I find more information?
The GEDI Mission webpage, and product specific user guides, associated and SDS Data Dictionaries, and Algorithm Theoretical Based Documents (ATBDs) have the most updated information respective to the latest version of the product. New product levels and derived datasets are forthcoming.
What Can GEDI Be Used For?
GEDI contributes a “missing piece,” the third-dimension, of surface structure tracking and plays a valuable role in weather forecasting, forest and fire management, biodiversity monitoring, and improvements of digital elevation models (DEMs). A continuously updated collection of GEDI-related research and other publications can be found on the GEDI webpage and zotero group here.
Watch this video of GEDI applied over the USA
Source: “The White House recently challenged the stewards of the public lands of the United States, including the Forest Service and the Bureau of Land Management, to produce the first ever national inventory of mature and old growth forests. The next phase of the project will be augmented by NASA laser altimetry data from an instrument on the International Space Station. The GEDI instrument can provide detailed information on tree height and forest biomass, not just in the U.S., but all around the globe.” (NASA Scientific Visualization Studio).
Topography and Surface Deformation
Capturing elevation, even below dense canopies, is one of GEDI’s key roles. Laser altimetry is notorious for its precise geolocation and definition of surface elevation. ICESat laser altimeters, by comparison, have been used to help validate and quantify errors in existing DEM (GEDI webpage applications).
Source: GEDI Mission.
Continental and Coastal Water Resources
Surface waters like inland seas, lakes, rivers, reservoirs, and wetlands, are commonly monitored with laser altimetry. Measuring the elevation of water bodies is important for hydrology studies regarding water volume change, in situ station leveling, wetland water level changes, river reach slopes, and river stage and discharge. GEDI provides sub-kilometer sampling of elevation outside of the water and for water in highly vegetated places.
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Source: Mangrove forest in Pongara National Park in Gabon, Africa, photographed during NASA’s 2016 AfriSAR mission (GEDI Mission).
Weather Prediction
Data for the detailed canopy structure and ground elevation can be used as biophysical variables in land surface models for weather predictions and forecasting. Regional radiation and evapotranspiration studies can use canopy gap (vegetation to ground ratios), surface roughness information from canopy heights, and plant area index. “Turbulence formation, heat and gas exchange, and aerosol dispersion in the biosphere-atmosphere boundary layer” can improve predictions (GEDI Mission).
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Source: “Meteorological effects of tree canopies. Credit: 2015 Franciszek Woch et al.” (GEDI Mission).
Fire Modeling
How much available fuel is there within a landscape, and is it mostly distributed horizontally or vertically? Managing landscapes and forests to address or prevent wildfires with prescribed burning strongly depends on an ability to characterize the structural components that could be set aflame. GEDI’s ability to capture localized at or near surface fuel characterization is an active area of research. The sampling density and spatial distribution over time enables land managers to test how well GEDI metrics are able to capture the efficacy of fuel treatments over a landscape. When applied to algorithms such as mapping canopy base height or canopy bulk densities, GED has the potential to help identify areas of high fire risk or ecosystem resilience to fire.
Source: Data flow for generation of GEDI-derived information products to aid managers and policy makers in assessments, monitoring and decision making related to wildland fire. Credit: Birgit Peterson. (GEDI Mission).
Habitat Quality and Biodiversity
The three-dimensional structure of forests is a key determinant of habitat quality, suitability, species distribution, richness, and abundance. GEDI provides crucial canopy structural measurements to quantify habitat and address the poor understanding of forest biological diversity at regional and global scales. GEDI provides much needed information for forest structure variations at regional scales, across climates, and under different levels of habitat disturbances. Pairing GEDI with direct wildlife observation data and combining the data with wall-to-wall mapping methods can enhance the detail of biodiversity information.
Source: “Bird species occurrence model in Sonoma County, California, using simulated GEDI data. (Courtesy of Burns et al. [2020])” (Data in Action, EarthData “A GEDI Master of the Bird World”).
Ecosystem Modeling and Management
Decisions regarding how ecosystems are managed are largely dictated by understanding of vegetation dynamics, as in “how, where, and what kind of vegetation grows in a given place” (GEDI Mission). Individual or landscape scale tree mapping for these kinds of models are facilitated with GEDI canopy height, plant area, plant area volume density, foliage height diversity, structural complexity estimations.
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Source: “Forest demographic processes represented by an individual based dynamic vegetation model (www.formind.org). Forest structure measurements from GEDI can be used to improve representation of these and other processes that influence the future of forests” (GEDI Mission).
Carbon Cycle Science
Forests play a critical role in regulating atmospheric CO2 concentrations by absorbing carbon. Accurate measurements of forest vertical structure are essential for assessing existing biomass, understanding changes in biomass due to human activities or climate variations, and quantifying carbon emissions from deforestation. GEDI data helps to compare large uncertainties in current global forest biomass estimates. It is imperative to evaluate the land surface’s role in disaster mitigation and adaptation strategies for projecting future carbon and biological resource management.
