Australian Geoscience Data Cube
/Presenter: Alexis McIntyre, Geoscience Australia
Wednesday, 16 November 2016
The Australian Geoscience Data Cube provides an integrated gridded data analysis environment for decades of analysis ready earth observation satellite, and related data from multiple satellite and other acquisition systems. It hosts the Australian Landsat Archive and other national Earth Observation collections, alongside access to gridded datasets such as rainfall and elevation.
This webinar demonstrates how to access the Australian Geoscience Data Cube using the Virtual Desktop Infrastructure (VDI) at the National Computational Infrastructure (NCI). By the end of the webinar you will be able to access national collections of Earth Observation data on the NCI, and use the Australian Geoscience Data Cube in a virtual desktop environment on the NCI.
To follow the presentation examples you will need to set up an account on the NCI, and set up access to the Virtual Desktop Infrastructure (VDI). Use project wd8 to sign up via https://nci.org.au/access/user-registration/register-new-user. Instructions on how to set up access to the VDI are available at http://vdi.nci.org.au/help. The Jupyter notebook used in the webinar can also be viewed here.
Joining project wd8 allows visualisation of all AGDC data on the NCI via the VDI, but restricts storage and computing abilities. If extra storage and computing resources are required in the future, this should be discussed with the AGDC or NCI teams. The AGDC can also be accessed within the High Performance Computing (HPC) environment (i.e. Raijin), and all users with computing quotas on Raijin are able to access the AGDC through the HPC system.
(Recording contains audio and visual [.flv file 106MB])
More resources:
Slack channel. (There is a link to sign-up, however if you are not part of an approved domain you will need an invitation. Please send a request to earth.observation@ga.gov.au.)
NCI data catalogue (which provides links to the metadata in the NCI GeoNetwork, and the data in THREDDS.)