Vegetation greenness every 16 days, 500 m (Terra)
What it measures. It measures how green and healthy plants are using two indices: NDVI (the classic greenness measure) and EVI (which works better in dense, lush vegetation). Each value is the best clear view from a 16-day window at 500-meter detail.
How it's made. Produced by ESA Copernicus from NASA's MODIS instrument on Terra, picking the cleanest pixels and computing vegetation indices as a Level-3 product.
How & where you'd use it. Widely used to track crop conditions, droughts, deforestation, and the timing of growing seasons, and to compare plant health year over year.
What's measured
Coverage & cadence
- Time span2000-02-18 → ongoing
- Spatial extent-180, -90, 180, 90
What you can do with it
- Map vegetation, forests and biomass
- Monitor ecosystem productivity and carbon
- Support habitat and biodiversity studies
Official description
The MODIS Terra MOD13A1 Version 6.1 product provides Vegetation Index (VI) values at 500 m spatial resolution on a per-pixel basis. The dataset includes two primary vegetation indices: the Normalized Difference Vegetation Index (NDVI), which serves as a continuity index with NDVI derived from NOAA-AVHRR observations, and the Enhanced Vegetation Index (EVI), designed to improve sensitivity in regions with high vegetation biomass. The product is generated as a 16-day composite, where the algorithm selects the best available pixel from all acquisitions within the compositing period based on criteria such as low cloud contamination, low view angle, and the highest NDVI/EVI value. Along with the vegetation index layers, the product includes two quality assurance layers, reflectance bands 1 (red), 2 (near-infrared), 3 (blue), and 7 (mid-infrared), as well as four observation layers.
Get the data
# ESA Copernicus Data Space — open STAC API (free account)
from pystac_client import Client
cat = Client.open("https://stac.dataspace.copernicus.eu/v1")
search = cat.search(
collections=["modis-terra-mod13a1"], # add _cog or _nc for a format variant
bbox=(-10, 35, 30, 60), # your area (W,S,E,N)
datetime="2024-01-01/2024-12-31",
)
items = list(search.items()) # then read assets with rioxarray / xarray Browsing the Copernicus STAC is open; downloading bytes needs a free Copernicus Data Space account.
Official links
- Open data source Copernicus STAC