Other teaching materials

[Peter9192]

Last week I was conducting some searches for geospatial analysis in Python. Many results and courses came up, but not this one. That made me wonder: (how) is this lesson different from other lessons? If yes: how can we improve its findability? If no: can we reduce the maintenance load by joining forces with other existing courses?

Here are some of the courses I found (sorted roughly according to my initial impression):

• PythonGIS: https://pythongis.org/index.html
• AutoGIS (same group?): https://autogis-site.readthedocs.io/en/latest/index.html
• SustainabilityGIS (same group?): https://sustainability-gis.readthedocs.io/en/latest/course-info/introduction.html
• Earthlab: https://www.earthdatascience.org/workshops/gis-open-source-python/
• PyGIS: https://pygis.io/docs/a_intro.html
• SpatialThoughs, particularly: https://spatialthoughts.com/courses/python-foundation-for-spatial-analysis/
• Spatial data programming with python: https://geobgu.xyz/py/
• IBM geospatial data: https://developer.ibm.com/learningpaths/data-analysis-using-python/introduction-to-geospatial-data-using-python/

[rogerkuou]

Hi @Peter9192, thanks for the comment! I spent some time browsing all the lessons you listed (I enjoyed this activity since most of them are good and relevant materials), and below are my thoughts on your comment.

As a general answer to your question, if this course differs from the examples, I will say: yes, the lesson materials are quite different from the listed materials. In my opinion, the uniqueness comes from the combination of the following characters:

• This is an instructor guide material for live coding, which means we will focus more on the interaction with students and give flexibility to allow students to ask questions along the way. Therefore, the material is not designed for the read & learn study. This already creates differences from most of the materials you listed.
• The duration of the workshop we are aiming at is ~2 full days, which is significantly shorter than the study time of many listed examples.
• The Python tools which can easily work with each other, e.g. pystac, rioxarray, geopandas, dask. These tools are either PanGeo package or their extensions. This is different from e.g. pygis which teaches geowombat, which is a good package but more stand alone.
• We are focusing on examples working locally without platform dependencies. This majorly differs from the IBM example.

And to further stress the question of whether we should make it more findable, my opinion would be, with reference to the first character: since this material is not meant for "read & learn", but for an instructor guide, we should focus on advertising it to instructors, but not to students. Then the effort I can think of, is to work more on getting this course to a steady sate and encourage more instructors to teach it. This is already on our radar. On May 26th, 2023 there will be a migration sprint.

Furthermore, I found the materials you shared are valuable for further reading after the workshop. Especially the PythonGIS, which gives a good walk through on Python basics, and more detailed explanations on the commands. Unfortunately, some parts of the material are still under construction. I am willing to point students at the end of workshop for further reading.