This chapter shows how to create and run workflow with a data source and analytics/processing algorithm.
First connect with UP42 as explained in the authentication chapter.
import up42
up42.authenticate(project_id="your project ID", project_api_key="your-project-API-key")
This simple workflow consists of Sentinel-2 L2A data and Sharpening Filter. See up42.get_blocks or the UP42 marketplace for all other data and analytics tasks.
project = up42.initialize_project()
workflow = project.create_workflow(name="Workflow-example")
workflow.add_workflow_tasks(["Sentinel-2 L2A Visual (GeoTIFF)",
"Sharpening Filter"])
Provide workflow input parameters to configure the workflow, e.g. the area of interest, time period etc. with the help of the construct_parameters function.
#aoi = up42.read_vector_file("data/aoi_berlin.geojson")
aoi = up42.get_example_aoi(location="Berlin")
input_parameters = workflow.construct_parameters(geometry=aoi,
geometry_operation="bbox",
start_date="2020-01-01",
end_date="2022-12-31",
limit=1)
input_parameters["esa-s2-l2a-gtiff-visual:1"].update({"max_cloud_cover":5})
Before running the workflow, estimate the costs. You can also run a free test job to confirm the correct job configuration and data availability.
workflow.estimate_job(input_parameters)
workflow.test_job(input_parameters, track_status=True)
job = workflow.run_job(input_parameters, track_status=True)
You can download and visualize the results via
job.download_results()
job.plot_results()