From a quick sandbox trial to a full production deployment — choose the path that works best for your needs.
Pre-configured Jupyter environment with sample Landsat and Sentinel-2 data. No installation — explore satellite imagery in your browser.
Launch Sandbox →Docker-based deployment with sample data and notebooks included. Ideal for evaluation and proof-of-concept projects.
View on GitHub →Production-grade setup with PostgreSQL backend. For national programs and large-scale satellite data processing.
Install Guide →The datacube-core library requires Python 3.9+ and PostgreSQL. It integrates with GDAL, xarray, and the full scientific Python ecosystem.
# Install with pip pip install datacube # Or with conda conda install -c conda-forge datacube
# Quick Docker setup git clone https://github.com/opendatacube/cube-in-a-box cd cube-in-a-box docker-compose up # → Jupyter at http://localhost:8888
Comprehensive API reference, configuration guides, and tutorials for datacube-core.
Read Docs →Interactive tutorials covering NDVI, water detection, land change, and satellite compositing.
View Notebooks →Step-by-step guides from ODC workshops and international training events.
Watch Videos →Ask questions and get help on GitHub Discussions and Slack channels.
Join Discussions →Our community is here to support you — from first install to production deployment.