GEDI L4A Raster Aboveground Biomass Density, Version 2.1

Dataset Availability

2019-03-25T00:00:00Z–2023-03-01T08:00:00Z

Dataset Provider

Rasterization: Google and USFS Laboratory for Applications of Remote Sensing in Ecology (LARSE) NASA GEDI mission, accessed through the USGS LP DAAC

Earth Engine Snippet

ee.ImageCollection("LARSE/GEDI/GEDI04_A_002_MONTHLY")

Tags

elevation gedi larse nasa tree-cover usgs

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

Resolution
25 meters

Bands

Name	Units	Description
agbd	Mg/ha	Predicted aboveground biomass density
agbd_pi_lower	Mg/ha	Lower prediction interval (see "alpha" attribute for the level)
agbd_pi_upper	Mg/ha	Upper prediction interval (see "alpha" attribute for the level)
agbd_se	Mg/ha	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	seconds	Time since Jan 1 00:00 2018
elev_lowestmode	m	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	deg	Latitude of center of lowest mode
lon_lowestmode	deg	Longitude of center of lowest mode
master_frac	seconds	Master time, fractional part. master_int+master_frac is equivalent to /BEAMXXXX/delta_time
master_int	seconds	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	deg	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	Mg/ha	Above ground biomass density; Geolocation latitude lowestmode
agbd_pi_lower_aN	Mg/ha	Above ground biomass density lower prediction interval
agbd_pi_upper_aN	Mg/ha	Above ground biomass density upper prediction interval
agbd_se_aN	Mg/ha	Aboveground biomass density prediction standard error
agbd_t_aN	Mg/ha	Aboveground biomass density model prediction in transform space
agbd_t_pi_lower_aN	Mg/ha	Lower prediction interval in transform space
agbd_t_pi_upper_aN	Mg/ha	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	m	Elevation of center of lowest mode relative to the reference ellipsoid
lat_lowestmode_aN	deg	Latitude of center of lowest mode
lon_lowestmode_aN	deg	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	pixel	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.

Explore with Earth Engine

Important: Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please register for Earth Engine access.

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');

Open in Code Editor

GEDI L4A Raster Aboveground Biomass Density, Version 2.1

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 …

LARSE/GEDI/GEDI04_A_002_MONTHLY, elevation,gedi,larse,nasa,tree-cover,usgs

2019-03-25T00:00:00Z/2023-03-01T08:00:00Z

-51.6 -180.0 51.6 180.0

Google Earth Engine

https://developers.google.com/earth-engine/datasets