Access and explore Zarr sample products

Browse available S1, S2, and S3 datasets, access them via cloud tools, and extend your workflow with open-source plugins.

STAC catalogue browser

Search, filter, and preview all available EOPF products. Also available programmatically via pystac-client.

Sentinel-1 Level-1 GRD

Sentinel-1 Level-1 GRD

Zarr

Focused SAR data, multi-looked and projected to ground range.

Sentinel-1 Level-1 SLC

Sentinel-1 Level-1 SLC

Zarr

Focused SAR data, geo-referenced using orbit and attitude data.

Sentinel-1 Level-2 OCN

Sentinel-1 Level-2 OCN

Zarr

Ocean products for wind, wave, and current applications.

Sentinel-2 Level-1C

Sentinel-2 Level-1C

Zarr

110×110 km tiles, ortho-images in UTM/WGS84 projection.

Sentinel-2 Level-1C (Zarr3 staging)

Sentinel-2 Level-1C (Zarr3 staging)

Zarr ZIP

110×110 km tiles, ortho-images in UTM/WGS84 projection.

Sentinel-2 Level-2A

Sentinel-2 Level-2A

Zarr

The Sentinel-2 Level-2A Collection 1 product provides orthorectified Surface Reflectance (Bottom-Of-Atmosphere: BOA).

Sentinel-3 OLCI Level-2 LFR

Sentinel-3 OLCI Level-2 LFR

Zarr

The Sentinel-3 OLCI L2 LFR product provides land and atmospheric geophysical parameters computed for full resolution.

View more collections in the STAC browser →

A robust framework for data analysis and computation

As part of the Sample Service, the EOPF Analytics Hub gives you a ready-made environment for working with EOPF Zarr data — no local setup required.

The notebook gallery is the starting point for putting it to use, with each notebook opening directly in JupyterHub, ready to run on Dask.

Explore the notebook gallery →

JupyterHub

Pre-configured JupyterLab environments with EOPF plugins already installed, plus a set of interactive notebooks to get started right away.

Dask

Parallel, data-proximate computing that runs next to the data itself, so you can process large Sentinel products without downloading them. Tightly integrated with JupyterHub.

Before you start

Access to the Analytics Hub uses your Copernicus Data Space Ecosystem (CDSE) identity. It's also accessible through the STAC Browser or programmatically via Python, Julia, and more.

Register on CDSE →

Access the data programmatically

Tip

Work in the cloud via JupyterHub when possible. Since Zarr's chunked format is designed for lazy remote access, direct download is not recommended.

import matplotlib.pyplot as plt
import xarray as xr

product_url = "https://data.eodc.eu/collections/EOPF_ZARR/products/cpm_v270/S02MSIL2A/2026/08/17/S2A_MSIL2A_20260817T101041_N0512_R022_T33TUL_20260817T165521.zarr"
ds = xr.open_dataset(product_url,
    engine="eopf-zarr",
    chunks="auto"
)
ds["b04"].plot()
plt.show()

Please use the STAC browser or the pystac client as a discovery tool for fetching the latest product URLs. More detailed examples can be found in the notebook gallery.

Tools & integrations

Use EOPF Zarr products inside your existing toolchain. All plugins are open-source and maintained on GitHub.

Find more information here.

xarray backendAn xarray backend implementation for ESA EOPF data products in Zarr format. GitHub PyPI Anaconda Docs
xcube data storexcube-eopf is a Python package and xcube plugin that adds a data store named “eopf-zarr” to xcube. GitHub PyPI Anaconda Docs
GDAL readerThe EOPF GDAL Plugin, a community-driven effort to extend GDAL with support for the EOPF (Earth Observation Processing Framework). GitHub
Julia readerThis project provides easy-to-use access to the new EOPF Zarr Sentinel ESA Remote Sensing data. GitHub
Reader for SNAPA prototype SNAP reader has been developed for the new EOPF Sentinel-2 Level-2A Zarr sample products, provided by the EOPF Zarr Sample Service. GitHub Installation guide

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