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Annual Aboveground Biomass for Boreal Forests of ABoVE Core Domain, 1984-2014

Submitted by ORNL DAAC Staff on 2021-06-06
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Spatial distribution of predicted aboveground biomass (AGB) density averaged over 1984-2014 for the ABoVE Core Study Domain. Ecoregions represent the EPA Level 2 Ecoregion boundaries. Source: Wang et al. (2021)

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Estimated annual AGB density for live woody species in the ABoVE Core Study Domain from 1984-2014.

New data for MODIS and FLUXNET-derived Global Daily Terrestrial Gross Primary Production

Submitted by ORNL DAAC Staff on 2021-05-21
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Gross primary production from FluxSat v2.0 expressed as carbon (g m-2 d-1) for July 1st, 2019.

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Version 2 of the dataset on satellite- and FLUXNET tower-derived data on daily gross primary production of global vegetation has been released.

Pre-Delta-X: AVIRIS-NG/UAVSAR AGB, AVIRIS-NG TSS and Surface Reflectance

Submitted by ORNL DAAC Staff on 2021-04-05
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Pre-DeltaX image highlights: AVIRIS-NG/UAVSAR Biomass (upper left), AVIRIS-NG Total Suspended Solids (lower left), and AVIRIS-NG Surface Reflectance (right).

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Pre-Delta-X Campaign datasets now available: AGB from AVIRIS-NG/UAVSAR, surface reflectance and total suspended solids from AVIRIS-NG.

High-Quality Forest Inventory Data for Gabon, Africa

Submitted by welchjn@ornl.gov on 2020-09-28
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Gridded Land, Vegetation, and Ice Sensor (LVIS) instrument data products at 25 m spatial resolution over the Mondah Forest (left) and Mabounie (right) sites in Gabon.

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NASA's airborne Land, Vegetation, and Ice Sensor (LVIS) instrument was used to collect inventory data for Gabon's forests.

Sub-Saharan Africa High Res Woody Cover and Biomass Estimates

Submitted by ORNL DAAC Staff on 2020-07-19
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Estimates of woody biomass (tree and shrubs) at 1-km resolution in megagrams per hectare (Mg ha-1). Biomass was estimated from canopy cover, canopy height, and tree allometry.  Source: C.W. Ross

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Estimates of woody cover and biomass across sub-Saharan Africa were derived from observations, tree allometry equations, and remote-sensing products.

Improved LiDAR-derived Biomass for Sonoma County, CA

Submitted by ORNL DAAC Staff on 2020-07-06
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Estimated aboveground biomass (Mg/ha) for Sonoma County at 30 m spatial resolution with the 5th-95th percentile range and the standard deviation (SD) of per-pixel biomass estimates shown in the top left and bottom left, respectively.

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A new dataset used a parametric modeling approach to estimate biomass from airborne LiDAR data and field measurements.