Reproducible geospatial project layout
60 min
Cover environments, data folders, notebooks vs scripts, and CRS hygiene.
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Spatial Data Science
Reproducible Geospatial Workflows in Python
Teach faculty how to structure notebook-to-script geospatial pipelines for course projects.
advanced~24 hours
For faculty
Focuses on reproducible analysis: project layout, CRS hygiene, vector/raster IO, and lightweight automation.
Competencies
Spatial statistics
Analysis
Geospatial Python
Data Science
Web GIS publishing
Systems
Objectives
- Structure a geospatial analysis repository for classroom reuse.
- Automate common cleaning and CRS validation steps.
- Publish a lightweight interactive map from processed outputs.
Outcomes
- Ship a documented notebook and script that regenerate key figures.create
- Diagnose CRS and geometry validity issues before analysis.analyze
Theory sessions
Demo sessions
From messy notebook to modules
50 min
Live refactor of a notebook into functions with schema assertions.
Exercise sessions
Pipeline clinic
150 min
Refactor a messy notebook into modular functions with assertions for CRS and schema.
Mini map publish
120 min
Export cleaned GeoJSON and embed an interactive map in a short faculty brief.
Assessment methods
Project / portfolio
Submitted maps, notebooks, or analysis portfolio.
Peer assessment
Structured review of classmates’ maps or reports.
Capstone / mini-project
End-of-course integrated geospatial project.