How much carbon high-latitude forests store (ICESat-2, 2020)
What it measures. Estimates how much carbon is locked up in the woody parts of far-northern forests, mapped at 30 m detail as aboveground biomass density. It also includes per-pixel uncertainty.
How it's made. Built by combining ICESat-2 laser measurements of forest height with field plot data and Landsat/Sentinel-2 and elevation imagery, using statistical and machine-learning models for the circa-2020 period.
How & where you'd use it. Helps scientists understand and monitor forest carbon stocks in boreal regions, filling a northern data gap important for climate-change research and forest management.
What's measured
Coverage & cadence
- Time span2019-06-01 → 2021-09-30
- Measured byICESat-2 (ATLAS) · Sentinel-2A (Sentinel-2 MSI)
- Processing levelLevel 4
- Spatial extent-179.818, 43.705, 178.399, 78.5313
- Formatsmultiple
- StatusCOMPLETE
What you can do with it
- Map vegetation, forests and biomass
- Monitor ecosystem productivity and carbon
- Support habitat and biodiversity studies
Official description
This dataset provides estimates of Aboveground dry woody Biomass Density (AGBD) for high northern latitude forests at a 30-m spatial resolution. It is designed both for boreal-wide mapping and filling the northern spatial data gap from NASA's Global Ecosystem Dynamics Investigation (GEDI) project. Mapping forest aboveground biomass is essential for understanding, monitoring, and managing forest carbon stocks toward climate change mitigation. The AGBD estimates cover the extent of high latitude boreal forests and extend southward to 50 degrees latitude outside the boreal zone. AGBD was predicted using two modeling steps: 1) Ordinary Least Squares (OLS) regression related field plot measurements of AGBD to NASA's ICESat-2 30-m lidar samples, and 2) random forest models were used to extend estimates beyond the field plots by relating ICESat-2 AGBD predictions to wall-to-wall covariate stacks from Harmonized Landsat Sentinel-2 (HLS) and the Copernicus DEM. Per-pixel uncertainties are estimated from bootstrapping both models. Non-vegetated areas (e.g. built up, water, rock, ice) were masked out. HLS composites and ICESat-2 data were from 2019-2021; three years of conditions were aggregated into the circa 2020 map. ICESat-2 data were filtered to include only strong beams, growing seasons (June through September), solar elevations less than 5 degrees, snow free land (snow flag set to 1), and "msw_flag" equal to 0 (clear skies and no observed atmospheric scattering). ICESat-2's ATL08 product was resampled to a 30-m spatial resolution to better match both the field plots and mapped pixels. HLS data (L30HLS) were used to create a greenest pixel composite of growing season multispectral data, which was then used to compute a suite of vegetation indices: NDVI, NDWI, NBR, NBR2, TCW, TCG. These were then used, in combination with the slope and elevation data from the Copernicus DEM product, to predict 30-m AGBD per 90-km tile. Estimates of mean AGBD with standard deviation are provided in cloud-optimized GeoTIFF (CoG) format. Training data are in comma-separated values (CSV) format. A polygon map of data tiles is included as a GeoPackage file and a Shapefile.
Get the data
import earthaccess
earthaccess.login(strategy="netrc") # free Earthdata Login
results = earthaccess.search_data(
short_name="Boreal_AGB_Density_ICESat2_2186",
version="1",
bounding_box=(-122.5, 37.2, -121.8, 37.9), # your area (W,S,E,N)
temporal=("2024-01-01", "2024-12-31"), # your dates
)
files = earthaccess.open(results) # stream straight from ORNL_CLOUDBrowsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package. Official links
- Earthdata Search allows users to search, discover, visualize, refine, and access NASA Earth Observation data. GET DATA
- ORNL DAAC Data Set Documentation VIEW RELATED INFORMATION
- Aboveground Biomass Density for High Latitude Forests from ICESat-2, 2020: Boreal_AGB_Density_ICESat2.pdf VIEW RELATED INFORMATION