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Full catalog/MOD09Q1G_EVI
MOD09Q1G_EVI·v6·dataset

How green the land is, gap-filled (Terra, 250 m)

MODIS/Terra Gap-Filled, Smoothed EVI 8-Day L4 250m SIN Grid
land NASA LAADS Level 4 active HDF-EOS
In plain English

What it measures. A measure of how green and vigorous the land's vegetation is, with the usual gaps and noisy spots filled in to give a clean, continuous picture every 8 days at 250-meter detail.

How it's made. Calculated from Terra MODIS surface-reflectance data, then run through smoothing and gap-filling steps to replace cloudy or poor-quality pixels.

How & where you'd use it. Valued by modelers who need uninterrupted vegetation data, for example to study carbon, water, and energy cycles across landscapes.

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 250m SIN Grid product, with short-name MOD09Q1G_NDVI is calculated from MODIS surface reflectance products (MOD09), at 250-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

mod09q1g_evi_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="MOD09Q1G_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.