Overview

ODC ECOSYSTEM

GEOSPATIAL DATA MANAGEMENT & ANALYSIS SOFTWARE

ODC CORE

ODC ALGORITHMS

ODC APPS

SATELLITE DATA

Examples:

  • Landsat

  • Sentinel

  • MODIS

FLEXIBLE DEPLOYMENT

Depending on your application, the Open Data Cube can be deployed on HPC, Cloud, and local installations. Typical installations run on Llnux, MacOS, and Windows.

INFORMED DECISIONS

Examples:

  • Deforestation

  • Water Quality

  • Illegal Mining

The Open Data Cube (ODC) is an open source solution for accessing, managing, and analyzing large quantities of Geographic Information System (GIS) data - namely Earth observation (EO) data. It presents a common analytical framework composed of a series of data structures and tools which facilitate the organization and analysis of large gridded data collections.

 

The Open Data Cube was developed for the analysis of temporally-rich earth observation data, however the flexibility of the platform also allows other gridded data collections to be included and analyzed. Such data may include elevation models, geophysical grids, interpolated surfaces and model outputs.

 

A key characteristic of the Open Data Cube is that every unique observation is kept, which contrasts with many other methods used to handle large gridded data collections. Some of the major advantages of ODC are the following:

  • Flexible framework

  • User maintains control and ownership over their data

  • Paradigm shift from scene-based analysis to pixel based

  • Lower barrier to entry for remote sensing data analysis.

In our technical overview document, we briefly describe and illustrate the high-level architecture and ecosystem of the ODC framework in order to provide a better understanding to those who are new to ODC. This document only covers major components of the ODC and the relationships between them. Find it here>>

What can it do?
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 license.

TECHNICAL OVERVIEW

WHAT IS IT CURRENTLY 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.

Elsewhere:
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.

OPEN DATA CUBE TOOLS  & APPLICATIONS

The ODC core serves as a layer between satellite data providers and applications. A set of open source tools exist to help scientists conduct research using data managed by the ODC. The figure below illustrates popular tools used within the community that utilizes the ODC Core as its basis:

  • Command Line Tools: A tool used by programmers/developers to interface with the ODC.

  • Open Data Cube Explorer: A visual and interactive web application that lets users explore their inventory of available data.

  • Open Data Cube Stats: An optimized means of defining and executing advanced analysis on ODC system. This tool is oriented towards scientists.

  • Web User Interface (UI): A web application that allows developers to interactively showcase and visualize the output of algorithms. 

  • Jupyter Notebooks: Research documents centered around techniques in EO sciences. A notebook contains executable code detailing examples of how the data cube is used in a research setting, and therefore is an invaluable reference material for new users.

  • Open Geospatial Consortium (OGC) Web Services: Adapters that can connect non-ODC applications to the ODC.