Repository for Digital Earth Australia Jupyter Notebooks: tools and workflows for geospatial analysis with Open Data Cube and Xarray

Tool to convert geopandas vector data into rasterized xarray data.

Repository for Digital Earth Africa Sandbox, including: Jupyter notebooks, scripts, tools and workflows for geospatial analysis with Open Data Cube and xarray

Useful tools and libraries for working with Open Datacube

Web-based exploration of Open Data Cube collections

Extracting tidally-constrained annual shorelines and robust rates of coastal change from freely available Earth observation data at continental scale

Dataset to Dataset Transformations

General purpose Docker Images related to the Open Data Cube project

National Intertidal Digital Elevation Model (NIDEM): a continental-scale elevation dataset for Australia's exposed intertidal zone

odcr is an R package that serves as an interface to the Open Data Cube.

Tools for extracting and preparing Digital Earth Australia Satellite Multi-Spectral Images for use in Deep Learning Machine models.

This repository hosts all you need to install an Open Data Cube instance as a docker container that serves a Jupyter notebook environment running both a Python kernel and an R kernel.

datacube-classification is a Python package developed to apply the time-first, space-later approach to indexed Earth Observation Data Cubes within the Open Data Cube ecosystem.

Pytest database fixtures for ODC Application Testing

stac2odc is a tool created to facilitate indexing data in the Open Data Cube using the information provided by STAC catalogs.

A tool created to facilitate indexing data in the Open Data Cube using the information provided by STAC catalogs.

Docker images to routinely generate derived EO products using the Open Data Cube and Dask

Web Platform for time series analysis of spatial data using spatial data cube

Docker image to provide a Data Cube instance access to distributed computing

Resources for deploying JupyterHub on Kubernetes with SatApps branding