Open Source GIScience

Joseph Holler's Open Source GIScience Resources at Middlebury College

COVID-19 Spatial Accessibility Reproduction

Oct-21 : In this lesson, we will reproduce COVID-19 spatial accessibility.

The goal of this lab is to get accustomed to working in a cyberinfrastructure environment with Python, Jupyter notebooks, and GitHub integration. We will do so with the Jupyter notebook published to accompany Kang et al (2020). The notebook has been published on CyberGISX and maintained in a GitHub repository

By the end of lab, you should have:

Advice:

Transitioning to next week you should:

Integrating GitHub with CyberGISX

Below I will outline three workflows. Geog 323 students, please just follow the first two. The third is for reference.

  1. Cloning a GitHub repository into CyberGISX
  2. Making changes on CyberGISX and pushing them to GitHub
  3. Pushing a CyberGISX project to a new GitHub repository

note: update instructions below with:

Cloning a GitHub repository into CyberGISX

Making changes on CyberGISX and pushing them to GitHub

Pushing a CyberGISX project to a GitHub repository

Now that the notebook has been copied into your CyberGISX account, you need a GitHub repository for this project.

Now the harder part: connecting the CyberGISX notebook to your GitHub repository using the Linux terminal and command line Git. Linux is an open-source operating system and its file and folder names are case-sensitive.

Helpful References

Reference

Kang, J. Y., A. Michels, F. Lyu, Shaohua Wang, N. Agbodo, V. L. Freeman, and Shaowen Wang. 2020. Rapidly measuring spatial accessibility of COVID-19 healthcare resources: a case study of Illinois, USA. International Journal of Health Geographics 19 (1):1–17. DOI:10.1186/s12942-020-00229-x.

Main Page