Sentinel-1 Coherence

This process generates a time series of Sentinel‑1 interferometric coherence for a set of interferometric pairs. The area of interest is specified at burst level using the Sentinel‑1 burst_id and sub_swath, ensuring precise spatial targeting and consistent acquisition geometry across the time series. Interferometric pairs are automatically defined by specifying a temporal extent and temporal baseline. The workflow is implemented using ESA SNAP operators and is defined as a Common Workflow Language (CWL) pipeline sar_coherence.cwl. Interferometric coherence provides a quantitative measure of phase stability between acquisitions and is widely used to assess surface change and temporal decorrelation driven by factors such as snow cover, vegetation dynamics, surface moisture, or mass movement. Coherence time series can be used for a variety of scientific and operational applications, including land cover classification, change detection, and as a diagnostic input for more advanced SAR analysis workflows.

An example on how to use it:

import openeo

connection = openeo.connect("openeo.dataspace.copernicus.eu/").authenticate_oidc()
stac_resource = connection.datacube_from_process(
    "sentinel1_sar_coherence",
    namespace="https://raw.githubusercontent.com/ESA-APEx/apex_algorithms/refs/heads/main/algorithm_catalog/eurac/sentinel1_sar_coherence/openeo_udp/sentinel1_sar_coherence.json",
    **{
        "temporal_extent": ["2018-01-28", "2018-02-04"],
        "temporal_baseline": 6,
        "burst_id": 329488,
        "coherence_window_az": 2,
        "coherence_window_rg": 10,
        "polarization": "VH",
        "sub_swath": "IW2"
    }
)

job = stac_resource.create_job(title="sentinel1_sar_coherence test")
job.start_and_wait()
job.get_results().download_files()