Cloud-free Landsat picture of Earth, every 2 months
What it measures. It offers seamless, cloud-free views of the land in Landsat's color bands at a detailed 30-meter resolution, refreshed every two months and stretching back to 1997. Missing pixels have been reconstructed to fill cloud gaps.
How it's made. Assembled by ESA Copernicus from the long-running Landsat satellite archive, aggregating analysis-ready imagery over time and filling gaps to create a continuous historical mosaic.
How & where you'd use it. Great for studying long-term land change such as urban sprawl, deforestation, and agriculture, and for any work needing consistent, gap-free historical imagery.
What's measured
Coverage & cadence
- Time span1997-01-01 → 2024-12-31
- Spatial extent-180, -90, 180, 90
What you can do with it
- Track deforestation, fire scars and land-cover change
- Monitor crop and vegetation health (NDVI/EVI)
- Map how built-up vs. green an area is over time
Official description
Global, cloud-free, and reconstructed historical Landsat spectral bands are provided at a spatial resolution of 30 meters and temporal resolution of bimonthly intervals from 1997 onwards. The dataset was generated using the GLAD Landsat ARD version 2 as the primary input for temporal aggregation and the imputation of missing values.
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=["opengeohub-landsat-bimonthly-mosaic-v1.0.1"], # 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 / xarrayBrowsing the Copernicus STAC is open; downloading bytes needs a free Copernicus Data Space account.
Official links
- Open data source Copernicus STAC