A QGIS desktop in the cloud with JupyterHub

JupyterHub is a versatile platform that can serve a desktop with Geospatial Information Systems (GIS) software in the cloud. This was demonstrated by the QGreenland Researcher Workshop that was hosted by the NASA CryoCloud hub. The hands-on workshop trained 25-30 researchers, from Germany, India, France, Canada, Poland and the United States, on how to work with geospatial data in an open science framework.

QGreenland Overview #

QGreenland is an open-source geospatial data package designed for QGIS, a community-owned GIS platform. It focuses on Greenland, offering researchers and educators a comprehensive toolset for FAIR (findable, accessible, interoperable and reproducible) data analysis. The package integrates a variety of datasets into a single, easy-to-use data-viewing and analysis platform, supporting both offline and online use. This makes it particularly valuable for remote fieldwork and areas with limited internet access.

Workshop Success #

The QGreenland workshop demonstrated several key benefits of using JupyterHub for cloud-based GIS:

• Accessibility: Participants from across the world could access the same powerful GIS tools through a web browser, eliminating the need for complex local installations while enhancing reproducibility
• Cloud block storage: Using a JupyterHub in the cloud allowed for faster data access than a traditional NFS file store by provisioning each user with an elastic block store disk, reducing load times from 5 minutes to under 3 seconds.
• Cost Efficiency: Utilizing the CryoCloud JupyterHub instance managed by 2i2c drastically cut down setup costs and time, with only minimal cloud operating expenses of roughly $1/person/day.

Conclusion #

The success of the QGreenland workshop underscores the potential of integrating interactive software applications in JupyterHub. This approach not only democratizes access to advanced geospatial tools but also fosters a collaborative research environment. We look forward to supporting more workshops for QGreenland in the future!

Want to know more? Check out the companion post by QGreenland on the Jupyter Blog

Acknowledgements #

• Trey Stafford (CIRES)
• Matthew Fisher (CIRES)
• *Fisher, M., *T. Stafford, T. Moon, and A. Thurber (2023). QGreenland (v3) [software], National Snow and Ice Data Center.
• Snow, Tasha, Millstein, Joanna, Scheick, Jessica, Sauthoff, Wilson, Leong, Wei Ji, Colliander, James, Pérez, Fernando, James Munroe, Felikson, Denis, Sutterley, Tyler, & Siegfried, Matthew. (2023). CryoCloud JupyterBook (2023.01.26). Zenodo. 10.5281/zenodo.7576602

* Denotes co-equal lead authorship