top of page

Empowering Global Insights:

Open Source Earth Observation at Scale

The Open Data Cube (ODC) is a free, open-source software platform that simplifies the management and analysis of large amounts of satellite imagery and other Earth observation data. It allows users to easily access, process, and analyze decades of geographical data to track changes on Earth's surface over time. ODC is designed to help scientists, researchers, and government agencies make better-informed decisions about environmental issues, land use, and resource management.

 

Use Case Examples

Land Cover Mapping in Australia: Researchers used the Open Data Cube through Digital Earth Australia (DEA) to generate annual national-scale land cover maps of Australia, leveraging Landsat imagery from 1988-2020. This work implemented the FAO Land Cover Classification System (LCCS) Level 3 to produce six main land cover classes at 25m resolution, supporting environmental monitoring and policy-making.
Citation: Owers, C. J., et al. (2022). "Operational continental-scale land cover mapping of Australia using the Open Data Cube." International Journal of Digital Earth, 15(1), 1715-1737.

Core Technology:

    • Built on Python and PostgreSQL

    • Uses xarray for labeled multi-dimensional arrays

  • Data Model:

    • Implements a data cube model: space (x, y) + time (t) + measurements

    • Supports both pixel-based and object-based analysis

  • Data Indexing:

    • Utilizes PostgreSQL for efficient metadata indexing

    • Enables rapid querying of large spatio-temporal datasets

  • Supported Data Formats:

    • Input: GeoTIFF, COG, NetCDF, CSV, Etc. 

  • Data:

    • Simply leverage Analysis Ready Data (ARD)

    • Handles all raster data

  • Interoperability:

    • REST API for integration with web services and other software

    • Compatible with common GIS tools (QGIS, ArcGIS) through GDAL

  • Scalability:

    • Designed for deployment on high-performance computing clusters and cloud platforms

    • Leverages dask for parallel computing capabilities

  • Algorithm Implementation:

    • Allows custom algorithm development in Python

    • Includes pre-built algorithms for common analyses (e.g., NDVI calculation, change detection)

Explore ODC Resources
Institutional Partners:
image.png
image.png
image.png
image.png
image.png
image.png
image.png
bottom of page