Aggregations and Automation

This lesson covers spatial aggregations (joining data from one layer into another based on location) and workflow automation. You’ll also learn about two statistical pitfalls that affect how aggregated data should be interpreted.

What’s in This Lesson

1. Aggregation Effects: MAUP and ecological fallacy. Two concepts that affect how aggregated spatial data should be interpreted.
2. Spatial Aggregations: Using spatial joins to aggregate census data into neighbourhood boundaries, and normalising results for meaningful comparison.
3. Processing Toolbox: Navigating QGIS’s tool library and using the History panel to document your workflow.
4. Graphical Modeller: Packaging sequences of operations into reusable, shareable models.

Datasets

This lesson uses datasets from the datasets page.

Caution

We’ve prepared these datasets for you. When sourcing your own data, check that the licence permits your intended use and include attribution on derivative maps.