[Tutorial/Workflow/Doc] The Geospatial Stack

[TinasheMTapera]

🧾 Summary

Geospatial data science relies on some very important
and specific low level tools. This tutorial should provide the
minimum viable stack (MVS) for geospatial data science, and a
workflow for how to install it.

🎯 Learning Goals / Outcomes

What should a reader understand or be able to do after following this tutorial/workflow?

• Goal 1
• Goal 2
• Goal 3

📦 Required Tools, Packages, or Data

List any software packages, datasets, or computing platforms used (e.g., R, Python, FASRC, GeoPandas, etc.).

• Tools:
• Libraries:
• Data source(s):

📄 Outline / Structure

Provide a brief outline of the sections or steps in the document:

1. Introduction
2. Setup
3. Key Steps
4. Conclusion / Next Steps

🔗 Related Materials

Link to related GitHub repos, issues, lab protocols, or previous examples:

• example-link-1
• example-link-2

🚦Status & Next Steps

What is the current status?

• Proposal
• In Progress
• Ready for Review
• Completed

Any notes on who will write or review the content?

[TinasheMTapera]

So far, it seems that installing brew from webi gives us access to the ability to install low level tools at the user level, no module stuff required. Then, you can use the homebrew formula:

https://formulae.brew.sh/formula/gdal