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Full catalog/modis-terra-mod14a1
modis-terra-mod14a1·dataset

Daily active fire and hot-spot detections, 1 km (Terra)

MODIS Terra Thermal Anomalies Fire Daily L3 Global 1km
biosphere ESA ESA Copernicus active
In plain English

What it measures. It flags where fires are actively burning, day by day, at 1-kilometer resolution, and includes a measure of how intensely each fire is radiating heat. The data come bundled in 8-day files holding eight days of daily detections.

How it's made. Produced by ESA Copernicus from NASA's MODIS instrument on Terra, which spots thermal anomalies (unusually hot pixels) and packages them as a Level-3 product.

How & where you'd use it. Used by firefighting and emergency teams, land managers, and researchers to locate wildfires, gauge their intensity, and study fire patterns.

What's measured

MODISTerraNASASatelliteGlobalFireThermal AnomaliesActive Fire1kmMOD14A1

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 MOD14A1 Version 6.1 product provides information on thermal anomalies and active fires at 1 km spatial resolution as a Level-3 dataset. The product is generated as an 8-day composite, where each file contains fire observations from eight consecutive days of MODIS Terra data. The dataset includes science data layers such as a fire mask identifying active fire pixels, pixel quality indicators, maximum Fire Radiative Power (MaxFRP), and the position of the fire pixel within the satellite scan. Each layer contains daily per-pixel information for each of the eight days within the compositing period.

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-terra-mod14a1"],   # 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.