Let me share with the SNAP community a different approach when using SNAP Graphs to process EO data.
This approach is based on the Common Workflow Language (CWL):
The Common Workflow Language (CWL) is an open standard for describing analysis workflows and tools in a way that makes them portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments.
And relies on a container (docker) to run gpt against a set of EO data available on the local computer and a SNAP graph also available locally.
The idea is to rely on:
- CWL to orchestrate the volume mounts for the EO input data and generated results
- a docker container to avoid installing SNAP on the local machine
The execution environment could be a VM on the cloud with docker.
There are two examples:
- Sentinel-3 OLCI Level-2 binning into a Level-3 https://github.com/snap-contrib/cwl-snap-graph-l3binning
- Sentinel-1 GRD calibration https://github.com/snap-contrib/cwl-snap-graph-runner
The READMEs provide guidance and I’m happy to support users willing to give a go either here or via GitHub issues