Tutorial resources for learning how to design, draw, and communicate maps for GIScience, GeoAI, and spatial data science.
This repository is an open learning space under AutoGeoAI4Sci. It collects practical resources on cartography, map design, reproducible geospatial visualization, and AI-assisted mapping workflows.
| Resource | Description |
|---|---|
| Zoom recordings | Guest lecture recordings on map-making contributed by Zhaoxu Sui from Penn State. |
| Map-making roadmap | A first-pass outline for turning these materials into a structured tutorial. |
notes/ |
Space for lecture notes, summaries, and reading reflections. |
examples/ |
Space for map-making examples in GIS software, Python, R, or web mapping tools. |
assets/ |
Space for figures, screenshots, and map outputs used by the tutorials. |
Good maps are not just outputs from GIS software. They are visual arguments. This repository focuses on the decisions that turn spatial data into readable, useful, and honest maps:
- choosing a map purpose and audience
- selecting projections and coordinate reference systems
- preparing spatial data for visualization
- designing symbols, colors, legends, labels, and layouts
- making publication-quality figures
- building reproducible map workflows in code
- using AI tools to support, check, or accelerate map-making
The first materials in this repository are two Zoom recordings shared by Zhaoxu Sui from Penn State. They are listed in docs/zoom-recordings.md.
These recordings remain hosted on Penn State Zoom. Access may depend on the host settings for each recording.
Special thanks to Zhaoxu Sui (Penn State) for contributing the Zoom recording resources and allowing them to be listed for the AutoGeoAI4Sci community.
This repository is starting as a curated resource page. Future updates can add:
- cleaned lecture notes
- example maps
- software-specific tutorials
- reproducible notebooks
- prompts and checklists for AI-assisted map design
- links to cartography references and open datasets