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xcube EOPF Data Store

xcube-eopf is a Python package that extends xcube with a new data store called "eopf-zarr". This plugin enables the creation of analysis-ready data cubes (ARDC) from Sentinel products published by the EOPF Sentinel Zarr Sample Service.

Overview

Once installed, the package gives access to EOPF data products in an analysis-ready data cube format through the standard xcube data store interface. You can:

  • List available data sources
  • Check data availability
  • Get metadata of the data sources
  • View available open parameters for each source
  • Open data source directly as xcube Dataset

To explore all available functions, see the Python API.

The data retrieval process uses the EOPF STAC API, which allows querying observations over a specified time range and spatial extent. The resulting datasets are mosaicked per time step and stacked into a 3D spatiotemporal data cube.

Each data variable is returned as a chunked Dask array, supporting efficient out-of-core computations and visualization.

Internally, the package uses the xarray-eopf backend for reading, and leverages xcube to construct spatiotemporal analysis-ready data cubes.

Features

IMPORTANT
xcube-eopf is currently under active development.
Some features may be partially implemented or still in progress.

The EOPF xcube data store is designed to provide analysis-ready data cubes from the EOPF Sentinel Zarr samples for Sentinel-1, Sentinel-2, and Sentinel-3 missions. The main features are summarized below. A more in depth documentation is given in the User Guide.

Currently, support is focused on Sentinel-2 products.

Sentinel-1

Support for Sentinel-1 will be added in an upcoming release.

Sentinel-2

The current implementation supports two Sentinel-2 product levels, available as data_id values:

  • sentinel-2-l1c: Level-1C top-of-atmosphere reflectance
  • sentinel-2-l2a: Level-2A atmospherically corrected surface reflectance

Cube Generation Workflow

The workflow for building 3D analysis-ready cubes from Sentinel-2 products involves the following steps:

  1. Query products using the EOPF STAC API for a given time range and spatial extent.
  2. Retrieve observations as cloud-optimized Zarr chunks via the xarray-eopf backend.
  3. Mosaic spatial tiles into single images per timestamp.
  4. Stack the mosaicked scenes along the temporal axis to form a 3D cube.

Supported Variables

  • Surface reflectance bands:
    b01, b02, b03, b04, b05, b06, b07, b08, b8a, b09, b11, b12
  • Classification/Quality layers (L2A only):
    cld, scl, snw

Example: Sentinel-2 L2A 

from xcube.core.store import new_data_store

store = new_data_store("eopf-stac")
ds = store.open_data(
    data_id="sentinel-2-l2a",
    bbox=[9.7, 53.4, 10.3, 53.7],
    time_range=["2025-05-01", "2025-05-07"],
    spatial_res=10 / 111320,  # meters to degrees (approx.)
    crs="EPSG:4326",
    variables=["b02", "b03", "b04", "scl"],
)

Sentinel-3

Support for Sentinel-3 products will be added in an upcoming release.

License

The package is open source and released under the Apache 2.0 license license. ❤