Earth Data School
About
Full catalog/modis-terraaqua-mcd15a3h
modis-terraaqua-mcd15a3h·dataset

Leaf cover and light absorption, 4-day combined sensors

MODIS Terra and Aqua Leaf Area Index FPAR 4-Day L4 Global 500m
biosphere ESA ESA Copernicus active
In plain English

What it measures. It measures leaf area index and FPAR, the share of sunlight green leaves absorb, at 500-meter detail but with a quicker 4-day refresh by combining two satellites' views.

How it's made. Generated by ESA Copernicus from NASA's MODIS instruments on both Terra and Aqua, selecting the best pixels over each 4-day window as a Level-4 product.

How & where you'd use it. Good for closely following rapid vegetation changes, such as crop growth stages or fast greening, and for feeding models that need more frequent canopy data.

What's measured

MODISTerraAquaNASASatelliteGlobalVegetationLAIFPARLeaf Area Index500mMCD15A3H

Coverage & cadence

  • Time span2002-07-08 → 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 and Aqua MCD15A3H Version 6.1 product provides a 4-day composite of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) at 500 m spatial resolution. The dataset is generated by selecting the best available pixel from all acquisitions from both MODIS sensors onboard the Terra and Aqua satellites within the 4-day compositing period. LAI represents the one-sided green leaf area per unit ground area in broadleaf canopies and half the total needle surface area per unit ground area in coniferous canopies. FPAR describes the fraction of incoming photosynthetically active radiation (400-700 nm) absorbed by the green vegetation canopy.

Get the data

copernicus_access.py
# 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-terraaqua-mcd15a3h"],   # 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.