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Welcome to the Wiki for the Jupyter Notebooks of Digital Earth Australia.
To get started, see either of these articles.
- Register for an account on the NCI using the guide here
- Pay particular attention to the NCI Data Access Groups step of the guide. Joining these NCI projects allows you to have access to DEA's satellite datasets and derived products.
- At minimum, we recommend joining:
-
wd8
(to use the Virtual Desktop Intrastructure) -
xu18
(to use the latest Geoscience Australia Landsat Analysis Ready Data Collection 3) -
ka08
(to use the latest Geoscience Australia Sentinel-2 Analysis Ready Data Collection 3) -
jw04
(to use the latest Landsat Derivatives Collection 3 data, e.g. WO, FC) -
fk4
(to use legacy derived DEA products, e.g. NIDEM, ITEM, HLTC) -
if87
(to use legacy Geoscience Australia Sentinel-2 Analysis Ready Data Collection 1)
-
- Follow instructions here to set up the Virtual Desktop Infrastructure/VDI and install DEA
- If you run into problems with the VDI, check the latest FAQ
- Follow the instructions in Using git with DEA Notebooks to start writing your own notebooks or contribute back to the repository using
git
or Github.
Useful links:
- The Digital Earth Australia User Guide
- The Digital Earth Australia Glossary
- Join the Open Data Cube slack. This is a friendly and active community of Open Data Cube users who are always happy to help answer any questions about DEA, Open Data Cube,
xarray
and Python! - The DEA NCI and Sandbox environments both contain slightly different datasets. To see what data is available, use:
- DEA Explorer for browsing the data that is available within DEA's NCI environment
- DEA Sandbox Explorer for browsing the data that is available within DEA's Sandbox environment
- Explore DEA products in DEA Maps
External links:
- Very extensive page of resources for performing deep learning on satellite imagery
Updating this wiki: If you notice anything incorrect or out of date in this wiki, please feel free to make an edit!
License: All code in this repository is licensed under the Apache License, Version 2.0. Digital Earth Australia data is licensed under the Creative Commons by Attribution 4.0 license.
Contact: If you need assistance with any of the Jupyter Notebooks or Python code in this repository, please post a question on the Open Data Cube Discord chat or on the GIS Stack Exchange using the open-data-cube
tag (you can view previously asked questions here). If you would like to report an issue with any notebook, you can file one on Github.