Full catalog/DeciduousFractionl_CanopyCover_2296
DeciduousFractionl_CanopyCover_2296·v1·dataset

Tree and leaf-shedding cover in boreal North America (1992-2015)

Deciduous Fractional Cover and Tree Canopy Cover for Boreal North America, 1992-2015
biosphere NASA ORNL_CLOUD Level 3 COG
In plain English

What it measures. Maps of boreal North America showing what share of tree cover is from leaf-shedding (deciduous) trees and how much of the ground is covered by tree canopy overall, at 30-meter detail across 1992 to 2015.

How it's made. Created from seasonal Landsat surface-color composites fed into statistical (random forest) models trained on field samples from Alaska and Canada, with uncertainty estimates included.

How & where you'd use it. Supports studying how northern forests are composed and changing, including shifts between evergreen and deciduous trees.

What's measured

BIOSPHERE › ECOSYSTEMS › TERRESTRIAL ECOSYSTEMS › FORESTSBIOSPHERE › VEGETATION › CANOPY CHARACTERISTICSBIOSPHERE › VEGETATION › DECIDUOUS VEGETATION

Coverage & cadence

  • Time span1992-01-01 → 2015-12-31
  • Measured byLANDSAT-5 (TM) · LANDSAT-7 (ETM+) · LANDSAT-8 (OLI)
  • Processing levelLevel 3
  • Spatial extent-179.94, 39.9997, -49.9998, 80.25
  • FormatsCOG
  • 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 holds deciduous fraction and tree canopy cover at 30-m resolution over the North American boreal domain for 1992 to 2015. Deciduous fraction is the areal percentage of deciduous trees relative to all tree canopy cover within a pixel, and tree canopy cover is the areal percentage of a pixel that is covered by tree canopy. Deciduous fraction values are valid only for pixels with tree canopy cover >25 percent. Normalized difference vegetation index (NDVI)-based median-value image composites were derived from Landsat 5, 7, and 8 Collection 1 surface reflectance datasets for years 1987-1997, 1998-2002, 2003-2007, 2008-2012, and 2013-2018 to create composites for nominal years 1992, 2000, 2005, 2010, and 2015, respectively. These image composites were prepared for early spring, mid-summer, and mid-to-late fall seasons to identify key differences in deciduous and evergreen green-up amplitudes. Random Forest (RF) regression models were used to derive deciduous fraction and tree canopy cover from the image composites. These models were trained with data from in-situ samples across Alaska and Canada from a variety of studies. Seventy percent of the in-situ samples were used for training and 30% for validation. Per-pixel uncertainty for both deciduous fraction and tree canopy cover are included and were based on one standard deviation of output values across all decision trees in the RF regression. These datasets were developed as part of NASA's ABoVE project to capture forest composition changes over the North American boreal domain across the last several decades. The data are provided in GeoTIFF format.

Get the data

deciduousfractionl_canopycover_2296_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="DeciduousFractionl_CanopyCover_2296",
    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_CLOUD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.