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Full catalog/MOD09Q1P_NDVI
MOD09Q1P_NDVI·v6·dataset

How green the land gets through the year, NDVI (MODIS Terra, 250 m)

MODIS/Terra NDVI Phenology annual L4 250m SIN Grid
land NASA LAADS Level 4 active HDF-EOS
In plain English

What it measures. A smoothed, gap-filled record of how green the land is over the course of a year, captured through NDVI, a greenness index that rises and falls with plant growth. Resolution is 250 meters.

How it's made. Built from MODIS surface-reflectance data on NASA's Terra satellite: the 8-day reflectance product is turned into NDVI, then smoothed and gap-filled into an annual Level-4 product.

How & where you'd use it. Useful for tracking the seasonal cycle of vegetation, the timing of green-up and senescence, and year-to-year changes in plant growth across the landscape.

What's measured

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

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 NDVI Phenology annual L4 250m SIN Grid product, with short-name MOD09Q1P_NDVI is a Gap-filled Smoothed NDVI created from the MOD09A1 8-day Surface Reflectance product. The spatial resolution is 250 meter. MOD09Q1P_NDVI is stored in Hierarchical Data Format (HDF) with sinusodial projection, same as other standard MODIS land products.

Get the data

mod09q1p_ndvi_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="MOD09Q1P_NDVI",
    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.