Yearly plant growth and carbon map (Terra)
What it measures. It gives annual totals for both carbon captured by plants (gross productivity) and the carbon kept as new growth (net primary productivity), at 500-meter resolution, summarizing a full year of vegetation activity.
How it's made. Built by ESA Copernicus from NASA's MODIS instrument on Terra by adding up the 8-day readings over a year and patching gaps with interpolated leaf data, as a yearly Level-4 product released after the year ends.
How & where you'd use it. Used to estimate how much carbon ecosystems store each year, monitor forest and crop productivity over time, and support climate models.
What's measured
Coverage & cadence
- Time span2001-01-01 → 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 MOD17A3HGF Version 6.1 product provides annual estimates of Gross Primary Productivity (GPP) and Net Primary Productivity (NPP) at 500 m spatial resolution. The dataset is generated by summing all 8-day GPP and Net Photosynthesis (PSN) values from the MOD17A2H product over a given year, where PSN is calculated as GPP minus Maintenance Respiration (MR). The gap-filled product is produced at the end of each year once the complete annual MOD15A2H LAI/FPAR dataset becomes available. Poor-quality LAI/FPAR inputs are identified using quality control flags and replaced through linear interpolation to improve data consistency. Because of this processing approach, the dataset is not available in near-real time and is released only after the full yearly dataset has been completed.
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-mod17a3hgf"], # 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