- Dataset Availability
- 2019-03-25T00:00:00Z–2024-11-01T08:00:00Z
- Dataset Provider
- Rasterization: Google and USFS Laboratory for Applications of Remote Sensing in Ecology (LARSE) NASA GEDI mission, accessed through the USGS LP DAAC
- Tags
Description
This dataset contains Global Ecosystem Dynamics Investigation (GEDI) Level 4A (L4A) Version 2 predictions of the aboveground biomass density (AGBD; in Mg/ha) and estimates of the prediction standard error within each sampled geolocated laser footprint. In this version, the granules are in sub-orbits. Height metrics from simulated waveforms associated with field estimates of AGBD from multiple regions and plant functional types (PFTs) were compiled to generate a calibration dataset for models representing the combinations of world regions and PFTs (i.e., deciduous broadleaf trees, evergreen broadleaf trees, evergreen needleleaf trees, deciduous needleleaf trees, and the combination of grasslands, shrubs, and woodlands).The algorithm setting group selection used for GEDI02_A Version 2 has been modified for evergreen broadleaf trees in South America to reduce false positive errors resulting from the selection of waveform modes above ground elevation as the lowest mode. The dataset LARSE/GEDI/GEDI04_A_002_MONTHLY is a raster version of the original GEDI04_A product. The raster images are organized as monthly composites of individual orbits in the corresponding month.
See User Guide for more information.
The Global Ecosystem Dynamics Investigation GEDI mission aims to characterize ecosystem structure and dynamics to enable radically improved quantification and understanding of the Earth's carbon cycle and biodiversity. The GEDI instrument, attached to the International Space Station (ISS), collects data globally between 51.6° N and 51.6° S latitudes at the highest resolution and densest sampling of the 3-dimensional structure of the Earth. The GEDI instrument consists of three lasers producing a total of eight beam ground transects, which instantaneously sample eight ~25 m footprints spaced approximately every 60 m along-track.
| Product | Description |
|---|---|
| L2A Vector | LARSE/GEDI/GEDI02_A_002 |
| L2A Monthly raster | LARSE/GEDI/GEDI02_A_002_MONTHLY |
| L2A table index | LARSE/GEDI/GEDI02_A_002_INDEX |
| L2B Vector | LARSE/GEDI/GEDI02_B_002 |
| L2B Monthly raster | LARSE/GEDI/GEDI02_B_002_MONTHLY |
| L2B table index | LARSE/GEDI/GEDI02_B_002_INDEX |
| L4A Biomass Vector | LARSE/GEDI/GEDI04_A_002 |
| L4A Monthly raster | LARSE/GEDI/GEDI04_A_002_MONTHLY |
| L4A table index | LARSE/GEDI/GEDI04_A_002_INDEX |
| L4B Biomass | LARSE/GEDI/GEDI04_B_002 |
Bands
Pixel Size 25 meters
Bands
agbd
Predicted aboveground biomass density
agbd_pi_lower
Lower prediction interval (see "alpha" attribute for the level)
agbd_pi_upper
Upper prediction interval (see "alpha" attribute for the level)
agbd_se
Aboveground biomass density prediction standard error
agbd_t
Model prediction in fit units
agbd_t_se
Model prediction standard error in fit units (needed for calculation of custom prediction intervals)
algorithm_run_flag
The L4A algorithm is run if this flag is set to 1. This flag selects data that have sufficient waveform fidelity for AGBD estimation.
beam
Beam identifier
channel
Channel identifier
degrade_flag
Flag indicating degraded state of pointing and/or positioning information
delta_time
Time since Jan 1 00:00 2018
elev_lowestmode
Elevation of center of lowest mode relative to reference ellipsoid
l2_quality_flag
Flag identifying the most useful L2 data for biomass predictions
l4_quality_flag
Flag simplifying selection of most useful biomass predictions
lat_lowestmode
Latitude of center of lowest mode
lon_lowestmode
Longitude of center of lowest mode
master_frac
Master time, fractional part. master_int+master_frac is equivalent to /BEAMXXXX/delta_time
master_int
Master time, integer part. Seconds since master_time_epoch. master_int+master_frac is equivalent to /BEAMXXXX/delta_time',
predict_stratum
Prediction stratum identifier. Character ID of the prediction stratum name for the 1 km cell
predictor_limit_flag
Predictor value is outside the bounds of the training data (0=in bounds; 1=lower bound; 2=upper bound)
response_limit_flag
Prediction value is outside the bounds of the training data (0=in bounds; 1=lower bound; 2=upper bound)
selected_algorithm
Selected algorithm setting group
selected_mode
ID of mode selected as lowest non-noise mode
selected_mode_flag
Flag indicating status of selected_mode
sensitivity
Beam sensitivity. Maximum canopy cover that can be penetrated considering the SNR of the waveform
solar_elevation
Solar elevation angle
surface_flag
Indicates elev_lowestmode is within 300m of Digital Elevation Model (DEM) or Mean Sea Surface (MSS) elevation
shot_number
Shot number, a unique identifier. This field has the format of OOOOOBBRRGNNNNNNNN, where:
- OOOOO: Orbit number
- BB: Beam number
- RR: Reserved for future use
- G: Sub-orbit granule number
- NNNNNNNN: Shot index
shot_number_within_beam
Shot number within beam
agbd_aN
Above ground biomass density; Geolocation latitude lowestmode
agbd_pi_lower_aN
Above ground biomass density lower prediction interval
agbd_pi_upper_aN
Above ground biomass density upper prediction interval
agbd_se_aN
Aboveground biomass density prediction standard error
agbd_t_aN
Aboveground biomass density model prediction in transform space
agbd_t_pi_lower_aN
Lower prediction interval in transform space
agbd_t_pi_upper_aN
Upper prediction interval in transform space
agbd_t_se_aN
Model prediction standard error in fit units
algorithm_run_flag_aN
Algorithm run flag-this algorithm is run if this flag is set to 1. This flag selects data that have sufficient waveform fidelity for AGBD estimation
l2_quality_flag_aN
Flag identifying the most useful L2 data for biomass predictions'
l4_quality_flag_aN
Flag simplifying selection of most useful biomass predictions
predictor_limit_flag_aN
Predictor value is outside the bounds of the training data
response_limit_flag_aN
Prediction value is outside the bounds of the training data
selected_mode_aN
ID of mode selected as lowest non-noise mode
selected_mode_flag_aN
Flag indicating status of selected mode
elev_lowestmode_aN
Elevation of center of lowest mode relative to the reference ellipsoid
lat_lowestmode_aN
Latitude of center of lowest mode
lon_lowestmode_aN
Longitude of center of lowest mode
sensitivity_aN
Maximum canopy cover that can be penetrated considering the SNR of the waveform
stale_return_flag
Flag from digitizer indicating the real-time pulse detection algorithm did not detect a return signal above its detection threshold within the entire 10 km search window. The pulse location of the previous shot was used to select the telemetered waveform.
landsat_treecover
Tree cover in the year 2010, defined as canopy closure for all vegetation taller than 5 m in height (Hansen et al., 2013) and encoded as a percentage per output grid cell.
landsat_water_persistence
The percent UMD GLAD Landsat observations with classified surface water between 2018 and 2019. Values >80 usually represent permanent water while values <10 represent permanent land.
leaf_off_doy
GEDI 1 km EASE 2.0 grid leaf-off start day-of-year derived from the NPP VIIRS Global Land Surface Phenology Product.
leaf_off_flag
GEDI 1 km EASE 2.0 grid flag derived from leaf_off_doy, leaf_on_doy, and pft_class, indicating if the observation was recorded during leaf-off conditions in deciduous needleleaf or broadleaf forests and woodlands. 1=leaf-off, 0=leaf-on.
leaf_on_cycle
Flag that indicates the vegetation growing cycle for leaf-on observations. Values are 0=leaf-off conditions, 1=cycle 1, 2=cycle 2.
leaf_on_doy
GEDI 1 km EASE 2.0 grid leaf-on start day- of-year derived from the NPP VIIRS Global Land Surface Phenology product.
pft_class
GEDI 1 km EASE 2.0 grid Plant Functional Type (PFT) derived from the MODIS MCD12Q1v006 product. Values follow the Land Cover Type 5 Classification scheme.
region_class
GEDI 1 km EASE 2.0 grid world continental regions (0=Water, 1=Europe, 2=North Asia, 3=Australasia, 4=Africa, 5=South Asia, 6=South America, 7=North America).
urban_focal_window_size
The focal window size used to calculate urban_proportion. Values are 3 (3x3 pixel window size) or 5 (5x5 pixel window size).
urban_proportion
The percentage proportion of land area within a focal area surrounding each shot that is urban land cover. Urban land cover was derived from the DLR 12 m resolution TanDEM-X Global Urban Footprint Product.
Terms of Use
Terms of Use
This dataset is in the public domain and is available without restriction on use and distribution. See NASA's Earth Science Data & Information Policy for additional information.
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Code Editor (JavaScript)
var qualityMask = function ( im ) { return im . updateMask ( im . select ( 'l4_quality_flag' ). eq ( 1 )) . updateMask ( im . select ( 'degrade_flag' ). eq ( 0 )); }; var dataset = ee . ImageCollection ( 'LARSE/GEDI/GEDI04_A_002_MONTHLY' ) . map ( qualityMask ) . select ( 'solar_elevation' ); var gediVis = { min : 1 , max : 60 , palette : 'red, green, blue' , }; Map . setCenter ( 5.0198 , 51.7564 , 12 ); Map . addLayer ( dataset , gediVis , 'Solar Elevation' );
