Cloud computing with Open Data Cube and Python

This workshop broadly covered remote sensing data analysis using the Open Data Cube (ODC), developed by Geoscience Australia. We went over some important Python packages that the ODC is built upon: Numpy, Xarray, and Dask, and explored how they enable fast and scalable computation.

All the learning material used in this tutorial is available on the Digital Earth Australia Sandbox as Jupyter Notebooks. An account was required to participate, which can easily be created here.

Additional documentation for the DEA Sandbox is available here which includes useful guides, a dataset catalogue and examples.

If you missed the demonstration, the recording is available on our cloudstor site, email mitchel.rudge@uq.edu.au to get access.

About the presenter

The workshop was be presented by Tim Devereux.

Tim is a PhD candidate with the UQ Remote Sensing Research Centre (RSRC), and has a background in Environmental and Computational Sciences. His research is focused on the development of high fidelity digital representations of Australian forests for next generation simulations. He is also a demonstrator for the SEES advanced remote sensing course at UQ.