STAC Hackathon
Thanks for joining our two-day hackathon to help improve Digital Earth Australia’s (DEA) Notebooks!
The primary goal of the hackathon is to transition DEA-Notebooks to use odc-stac. This will be the first full repository refresh of DEA-Notebooks since 2019. A more detailed list of hackathon goals is outlined below.
- Convert DEA-Notebooks repo to use
odc-stac.loadrather thandatacube.load - Develop skills and knowledge on
odc-stac(and STAC more generally) - Further test, refine, and document alternate access patterns for DEA (e.g. CodeSpaces, Colab)
- Develop communications and KH articles on the update to DEA-Notebooks
- Address backlog DEA-Notebooks tasks (‘Issues’)
Day 1
9am
- Introduction
- Assign yourself (or small team) to tasks
- Get started!
Day 2
9am
- Open discussion on any issues encountered on Day 1
3.30pm
- Showcase of work
- Discuss next steps and timeline for approval and deployment of updated DEA-Notebooks
- Publication of JOSS paper timeline?
- Hackathon project board: See what needs doing, and what others are working on
- Prioritised notebook list: Shows which notebooks are highest priority for updating
- Set up instructions: How to get your environment running
-
develop_stacbranch: The branch we're working in - make sure you're on it! - DEA_notebooks_template: The latest notebook layout and style we are standardising on
- Introduction to loading data with STAC
- Using "load_ard" to load and cloud mask Landsat and Sentinel-2
- Introduction to DEA Surface Reflectance (Landsat, Collection 3)
- Monitoring coastal erosion along Australia's coastline
- Knowledge Hub article on STAC
- DEAfrica
odc-stacconversion repository - FrontierSI
odc-stacexample notebooks odc-stacdocs page- Introduction to STAC (with the Brazilian DataCube)
- odc-stac
load()andconfigure_s3_accessimported -
pystac_clientClientimported - environment setup includes
catalog,stac_clientandconfigure_s3_access() - cell that searched a collection for items with
pystac-client - cell that loads discovered items into an xarray with
odc-stac
Updating this wiki: If you notice anything incorrect or out of date in this wiki, please feel free to make an edit!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.