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Full catalog/MOD09A1G_EVI
MOD09A1G_EVI·v6·dataset

How green the land is, gap-filled (Terra, 500 m)

MODIS/Terra Gap-Filled, Smoothed EVI 8-Day L4 500m SIN Grid
land NASA LAADS Level 4 active HDF-EOS
In plain English

What it measures. A cleaned-up, gap-free measure of how green the land is, at 500-meter detail in 8-day steps, with clouds and other bad spots filled in so there are no holes.

How it's made. Calculated from MODIS surface-reflectance data on NASA's Terra satellite, then run through smoothing and gap-filling steps that replace missing or poor observations with the best available high-quality data.

How & where you'd use it. Made for modeling work that needs continuous, complete vegetation data, such as carbon and ecosystem models, where ordinary gappy satellite data would cause problems.

What's measured

LAND SURFACE › LAND USE/LAND COVER › LAND USE/LAND COVER CLASSIFICATION › VEGETATION INDEX

Coverage & cadence

  • Time span2001-01-01 → ongoing
  • Measured byTerra (MODIS)
  • Processing levelLevel 4
  • Spatial extent-180, -90, 180, 90
  • FormatsHDF-EOS
  • StatusACTIVE

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

The MODIS/Terra Gap-Filled, Smoothed NDVI 8-Day L4 500m SIN Grid product, with short-name MOD09A1G_NDVI is calculated from MODIS surface reflectance products (MOD09), at 500-m resolution. MODIS time series contains occasional lower quality data, gaps from persistent clouds, cloud contamination, and other gaps. Many modeling efforts, such as those used in NACP, that use MODIS data as input, require gap-free data. The procedure contains two algorithm stages, one for smoothing and one for gap filling, which attempt to maximize the use of high-quality data to replace missing or poor-quality observations.

Get the data

mod09a1g_evi_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="MOD09A1G_EVI",
    version="6",
    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 LAADS
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.