Analytics¶

Apply analytics on geospatial data by using workflows with data blocks and processing blocks.

Step 1. Create and populate a workflow¶

A workflow is a sequence of data blocks and processing blocks. It defines an order for operations.

A workflow starts with a data block, which may be followed by processing blocks. You can add one data block and up to five processing blocks to a workflow.

A workflow graph

Create a workflow and populate it with blocks, for example:

project = up42.initialize_project()

workflow = project.create_workflow(name="My workflow with Processing from Storage")
workflow.add_workflow_tasks([
  "Processing from Storage"
])

If needed, search for compatible blocks:
```
workflow.get_compatible_blocks()
```
The search outputs a dataframe with blocks that can be added to your workflow, for example:
```
workflow.add_workflow_tasks([
  "Sharpening Filter"
])
```

Step 2. Retrieve an input schema¶

Retrieve input parameters of the first block in a workflow:

workflow.get_parameters_info()

For example, Processing from Storage requires asset_ids as input parameters:

{
  "up42-processing-from-storage:1": {
    "asset_ids": {
      "type": "array",
      "default": "None",
      "required": true
    }
  }
}

Step 3. Configure an AOI¶

If you use storage data as a data source, skip this step.

# geometry = up42.read_vector_file("data/aoi_washington.geojson")
# geometry = up42.get_example_aoi()
geometry = {
    "type": "Polygon",
    "coordinates": (
      (
          (13.375966, 52.515068),
          (13.375966, 52.516639),
          (13.378314, 52.516639),
          (13.378314, 52.515068),
          (13.375966, 52.515068),
        ),
    ),
}

Step 4. Adjust JSON parameters¶

Define how data retrieval and analysis will be performed during a job run, for example:

input_parameters = workflow.construct_parameters(
    geometry=geometry,
    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})

Step 5. Make a test query¶

A test query doesn't consume credits. It searches for available data based on your parameters and provides JSON metadata and low resolution quicklooks of available images.

workflow.test_job(input_parameters, track_status=True)

Step 6. Get a cost estimate¶

Get a cost estimation before running a live job:

workflow.estimate_job(input_parameters)

Step 7. Run a job¶

job = workflow.run_job(input_parameters, track_status=True)

Step 8. Get results¶

You can download and visualize the results:

job.download_results()
job.plot_results()

Troubleshooting¶

How many blocks can I add to a workflow?¶

You can add one data block and up to five processing blocks to a workflow.