[Review]: Introduction to Geospatial Raster and Vector Data with Python

[rbavery]

Lesson Title

Introduction to Geospatial Raster and Vector Data with Python

Lesson Repository URL

https://github.com/carpentries-incubator/geospatial-python

Lesson Website URL

https://github.com/carpentries-incubator/geospatial-python

Lesson Description

The data used in this lesson includes optical satellite images from the Copernicus Sentinel-2 mission and public geographical datasets from the dedicated distribution platform of the Dutch government. These are real-world data sets that entail sufficient complexity to teach many aspects of data analysis and management. They have been selected to allow students to focus on the core ideas and skills being taught while offering the chance to encounter common challenges with geospatial data.

The lesson walks the learner through accessing, fetching, inspoecting, munging, and visualizing satellite imagery and geospatial vector data.

Author Usernames

@rbavery @fnattino @rogerkuou @mkuzak

Zenodo DOI

No response

Differences From Existing Lessons

This lesson was originally ported from the Geospatial R lesson, using the same datasets.

The lesson has been revamped to highlight python libraries for fetching raster and vector data from cloud hosted data stores and take advantage of the Cloud Optimized Geotiff format.

Confirmation of Lesson Requirements

• is the original work of the author(s), or that any content derived from another source is reused with permission and appropriate attribution
• aligns with The Carpentries Code of Conduct
• is published under a CC-BY or CC0 license
• uses The Carpentries lesson template or Carpentries Workbench without significant customisation/adaptation.

JOSE Submission Requirements

• the lesson repository includes paper.md and paper.bib files as described in the JOSE submission guide for learning modules

Potential Reviewers

Toby Hodges
Any other carpentries community members who are into geospatial!