Earth Data School
About
Full catalog/Global_Veg_Greenness_GIMMS_3G_2187
Global_Veg_Greenness_GIMMS_3G_2187·v1·dataset

How green the land has been since 1981 (NDVI)

Global Vegetation Greenness (NDVI) from AVHRR GIMMS-3G+, 1981-2022
land NASA ORNL_CLOUD Level 3 netCDF-4 classic
In plain English

What it measures. How green the land has been, expressed as a vegetation greenness index (NDVI) that rises with healthier, denser plant cover. It offers two snapshots per month from 1981 onward.

How it's made. Built from decades of measurements by the AVHRR sensors flown on a series of NOAA and MetOp weather satellites, carefully corrected for sensor drift, calibration changes, and even volcanic eruptions.

How & where you'd use it. A go-to long-term record for tracking vegetation trends, droughts, growing seasons, and the effects of climate change on plant life across the globe over forty-plus years.

What's measured

LAND SURFACE › LAND USE/LAND COVER › LAND USE/LAND COVER CLASSIFICATION › VEGETATION INDEXBIOSPHERE › VEGETATION › VEGETATION INDEX › NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI)

Coverage & cadence

  • Time span1982-01-01 → 2022-12-31
  • Measured byNOAA POES (AVHRR) · METOP-A (AVHRR) · METOP-B (AVHRR) · METOP-C (AVHRR)
  • Processing levelLevel 3
  • Spatial extent-180, -90, 180, 90
  • FormatsnetCDF-4 classic
  • StatusCOMPLETE

What you can do with it

  • Track deforestation, fire scars and land-cover change
  • Monitor crop and vegetation health (NDVI/EVI)
  • Map how built-up vs. green an area is over time
Official description

This dataset holds the Global Inventory Modeling and Mapping Studies-3rd Generation V1.2 (GIMMS-3G+) data for the Normalized Difference Vegetation Index (NDVI). NDVI was based on corrected and calibrated measurements from Advanced Very High Resolution Radiometer (AVHRR) data with a spatial resolution of 0.0833 degree and global coverage for 1982 to 2022. Maximum NDVI values are reported within twice monthly compositing periods (two values per month). The dataset was assembled from different AVHRR sensors and accounts for various deleterious effects, such as calibration loss, orbital drift, and volcanic eruptions. The data are provided in NetCDF format.

Get the data

global_veg_greenness_gimms_3g_2187_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="Global_Veg_Greenness_GIMMS_3G_2187",
    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.