This brick introduces automated geospatial pipelines using Apache Airflow—a powerful workflow engine for scheduling, monitoring, and scaling spatial data tasks.

 

You’ll get hands-on experience with real-world pipelines like:

 

  • Daily raster inference and tiling to PMTiles
  • Vector-to-GeoParquet transformation and catalog updates
Register & Get Started for $49
SPATIAL LAB CERTIFICATION

E3: Apache Airflow for Geospatial Automation

Brick E3 – Core Competencies (High-Level)

  1. Airflow DAG Design for Spatial Workflows
    Define and structure Directed Acyclic Graphs (DAGs) to automate geospatial ETL and inference tasks.
  2. Raster Inference Pipelines
    Run large-scale raster processing (e.g. snow detection) and export results as tiled PMTiles layers.
  3. Vector Data Transformation
    Convert CSV point data into GeoParquet, register geometry columns, and publish to spatial catalogs.
  4. CI-Friendly DAG Testing
    Write lightweight Pytest checks for DAG validity, task execution, and proof-of-completion artifacts.

What you'll learn

✅ The fundamentals of Airflow for orchestrating spatial data workflows.
✅ How to build DAGs for raster inference and vector-to-GeoParquet pipelines.
✅ Benefits of automation for reproducibility, scaling, and continuous delivery.

Learn by doing

You’ll learn by doing: coding inside a live cloud-based environment and running real code with best practices embedded.

Format

💻 4–6 hours to complete
🧪 Interactive notebook environment in Gitpod
✅ Autograded tests for completion
📛 Earn a verifiable Open Badge upon passing
🔁 Self-paced – start anytime
Lesson Skills

E3 Certified Skills

Full list of skills and tools used during this certification track. Anyone who has the validated badge for this track has used these tools and skills.

– Understand how Airflow schedules and runs tasks via Directed Acyclic Graphs (DAGs)
– Define DAGs with clear task dependencies, intervals, and retry logic

– Run daily raster processing (e.g., snow depth change detection) using Python or external tools
– Export processed rasters to tiled formats like PMTiles for fast web visualization

– Convert raw CSV or point data into GeoParquet
– Register geometry columns and structure outputs for spatial catalogs

– Use PythonOperators for custom geospatial tasks
– Integrate sensors and conditionals for flexible, event-driven pipelines

– Design DAGs for modularity and scalability across datasets
– Use @daily and catchup=False to simulate real-world production behavior

 

– Store resulting PM Tiles in S3 Storage
– Integrate AWS keys securely into the Airflow environment

Affordable plans

Flexible pricing to suit every team size

Choose from scalable pricing options that grow with your team’s needs and budget.

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E2 Brick

Learn the complete track and how to interweave skills in a Capstone seminar

$ 49
  • Full E1 Brick content
  • Certification badge on completion
  • Cloud resources and code
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Full Brick Track

Learn the complete track and how to interweave skills in a Capstone seminar

$ 149
  • Access to all 4 E-Track Bricks
  • Certifications for each Brick
  • Capstone seminar for the track
  • Capstone certifiation
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Modern GIS

Spatial Lab Membership

Get full access to additional tracks, community resources, and live cohort events.

$ 19 /month
  • Access to the E-Track and other upcoming tracks
  • Community supported learning with other learners
  • Access to live events for this track
  • Much more...
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