I know we’ve already discussed of Data Cubes technologies applied to earth observation data, but this is still an open subject in France.
I know we can leverage Pangeo to build server less Data cubes out of raw files with some coding, this has been demonstrated by @scottyhq et al with Landsat imagery. A year and a half ago we also began writing an article about Pangeo based data cubes vs Rasdaman kind of technologies.
I think, or at least colleagues of mine, that there’s still a missing piece, or it lacks some integration for non coders who just wants to explore and visualize big stack of images (usually time series), applying some filters or transformations on them.
I’ve recently heard of a new player based on Dask and xarray : xcube. Ever heard of it?
I had heard about xcube before, and I’m happy to see it advancing. It looks very cool and powerful!
On top of xarray, dask, zarr, and other popular Python data science packages, xcube provides various higher-level tools to generate, manipulate, and publish xcube datasets:
CLI - access, generate, modify, and analyse xcube datasets using the xcube tool;
Python API - access, generate, modify, and analyse xcube datasets via Python programs and notebooks;
Web API and Server - access, analyse, visualize xcube datasets via an xcube server;
Viewer App – publish and visualise xcube datasets using maps and time-series charts.
I would say this is a model project for building on top of and reusing the Pangeo stack, adding additional features needed by that community. I would say we should put our full support behind this project as a way for working with these types of data cubes.
Given xcube’s integration with open-eo, this is also closely related to my recent post
Open Data Cube I have used a little bit - they have a Slack, too. There’s a Cube In a Box container/cloud install that works pretty nicely you can have a look at, see their github.