What it can it do, and how to do it:
The Open Data Cube
What can it do
Introduction to Open Data Cube
Project Open Data Cube (ODC) is an open source project born out of the need to better manage Satellite Data. It provides the foundation of several international, regional to national scale data architecture solutions, such as Digital Earth Australia, Africa Regional Data Cube, and others.
The Data Cube works well with Analysis Ready Data (ARD), pre-processed, ready to use data made available by data providers. While providers work on making global ARD products available on the cloud, the Data Cube typically uses the USGS collection 1 Landsat 8 PDS for demonstrations. These data are not ARD and should not be used for scientific analysis. In 2019, it is expected ARD data will become easily available on the Cloud, and until then a user can simply add and index their own processed data. Any data available to you can be installed to your cube, including commercial, in situ, or derived products.
The Open Data Cube system is designed to:
- Catalogue large amounts of Earth Observation data
- Provide a Python based API for high performance querying and data access
- Give scientists and other users easy ability to perform Exploratory Data Analysis
- Allow scalable continent scale processing of the stored data
- Track the provenance of all the contained data to allow for quality control and updates
It has evolved to support interactive data science and scientific computing. ODC will always be 100% open source software, free for all to use and released under the liberal terms of the Apache 2.0 licence.
What is the Open Data Cube already doing?
Digital Earth Australia:
Digital Earth Australia is the Australian government's implementation of the open source analysis platform developed as part of the Open Data Cube (ODC) initiative. The DEA program contributes code, documentation, How-to guides, tutorials, and support to international users of the Open Data Cube.
Africa Regional Data Cube
The Africa Regional Datacube will support 5 countries in central Africa: Kenya, Senegal, Sierra Leone, Ghana and Tanzania. This effort is focused on building the capacity of users in this region to apply Earth observation satellite data to address local and national needs as well as the objectives of the Group on Earth Observations (GEO) and the United Nations Sustainable Development Goals (UN-SDG).
Swiss Data Cube
The Swiss Data Cube was one of the first adopters of the Data Cube system for a national scale platform. Beginning with 5 years of downloaded Landsat Analysis Ready Data in 2016, the now have over 30 years of Landsat, and now Sentinel 1 and Sentinel 2 over the entire country. New data are automatically updated daily as new scenes become available. Products of interest in the Swiss Data Cube are urbanization, cloud free mosaics, and snow cover.
Click on the Swiss Data Cube project, then press play. Use the arrow keys to scroll.
There are many other Data Cubes in development and operation, with a growing list of about 40 countries on our "Road to 20". These include the operational Colombian Cube, and projects in the US, Vietnam, the UK, and India.
How to do it
The ODC Sandbox
A demonstration Data Cube Sandbox is available as an entry point to getting started with the Open Data Cube, and was recently made available here(Link will be available when public). The Sandbox is a JupyterHub Python notebook server, with individual work spaces, and the Global Collection 1 Landsat 8 AWS PDS indexed.
See our ODC Sandbox page for more information.
The ODC Reference install - Cube in a Box
A distributable, ready to run reference install is available as the “ODC Reference Install”, or Cube in a Box (CIAB). Where the Sandbox install provides an accessible, externally managed platform to trial the features of the Open Data Cube, the Reference Install is designed to provide a ready to run installation of an independent Open Data Cube, on an organization's own resources.
See our Cube in a Box page for more information.
The Data Cube Applications Library
Both the Sandbox and the Reference Install come with a variety of ready-to-run applications, in the form of Python Jupyter Notebooks. The DCAL algorithms are available on the Data Cube Applications Library.