Monthly map of burned land, 500 m
What it measures. It maps which areas burned each month at 500-meter detail and records the exact day each patch burned, along with uncertainty and quality information.
How it's made. Created by ESA Copernicus from NASA's MODIS instruments on Terra and Aqua, combining surface reflectance with active-fire detections and a burn-sensitive index to spot scorched ground, as a monthly Level-3 product.
How & where you'd use it. Used to measure how much land wildfires consume, study fire seasons and emissions, and support post-fire recovery and land-management decisions.
What's measured
Coverage & cadence
- Time span2000-11-01 → 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 and Aqua MCD64A1 Version 6.1 product provides a global monthly burned area dataset at 500 m spatial resolution with per-pixel burn and quality information. The product is generated using MODIS Surface Reflectance imagery at 500 m resolution combined with 1 km MODIS active fire observations. The algorithm applies a burn-sensitive vegetation index derived from atmospherically corrected MODIS shortwave infrared reflectance bands 5 and 7 along with temporal texture analysis to detect burned areas. The dataset identifies the burn date for each 500 m grid cell within a MODIS tile, encoded as the ordinal day of the calendar year when the burn occurred, with additional values representing unburned land, water, or missing data. The product includes layers for Burn Date, Burn Date Uncertainty, Quality Assurance, and the First and Last Day of reliable change detection within the year.
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-terraaqua-mcd64a1"], # 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