10.3334/ORNLDAAC/1824
Baccini, A.
A.
Baccini
Walker, W.
W.
Walker
Carvalho, L.E.
L.E.
Carvalho
Farina, M.K.
M.K.
Farina
Solvik, K.K.
K.K.
Solvik
Sulla-Menashe, D.
D.
Sulla-Menashe
Aboveground Biomass Change for Amazon Basin, Mexico, and Pantropical Belt, 2003-2016
Carbon Monitoring System (CMS)
ORNL Distributed Active Archive Center
2021
BIOSPHERE, ECOLOGICAL DYNAMICS, ECOSYSTEM FUNCTIONS, BIOMASS DYNAMICS
BIOSPHERE, VEGETATION, CARBON,
BIOSPHERE, VEGETATION, BIOMASS,
ICESat, GLAS
Aqua, MODIS
Terra, MODIS
Environmental Modeling, Computer
machine learning
MODIS
WorldClim
GLAS
SoilGrids
carbon stock
woody biomass
LiDAR
ORNL DAAC
2021-02-27
2021-02-27
2003-01-01/2016-12-31
en
https://daac.ornl.gov/cgi-bin/dataset_lister.pl?p=33
Data Files
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GTiff
This dataset provides gridded estimates of aboveground biomass (AGB) for live dry woody vegetation density in the form of both stock for the baseline year 2003 and annual change in stock from 2003 to 2016. Data are at a spatial resolution of approximately 500 m (463.31 m; 21.47 ha) for three geographies: the biogeographical limit of the Amazon Basin, the country of Mexico, and a Pantropical belt from 40 degrees North to 30 degrees South latitudes. Estimates were derived from a multi-step modeling approach that combined field measurements with co-located LiDAR data from NASA ICESat Geoscience Laser Altimeter System (GLAS) to calibrate a machine-learning (ML) algorithm that generated spatially explicit annual estimates of AGB density. ML inputs included a suite of satellite and ancillary spatial predictor variables compiled as wall-to-wall raster mosaics, including MODIS products, WorldClim climate variables reflecting current (1960-1990) climatic conditions, and SoilGrids soil variables. The 14-year time series was analyzed at the grid cell (~500 m) level with a change point-fitting algorithm to quantify annual losses and gains in AGB. Estimates of AGB and change can be used to derive total losses, gains, and the net change in aboveground carbon density over the study period as well as annual estimates of carbon stock.
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