Lots of optical microscopy (and I think also some satellite imaging). Often these are quite well registered (i.e. aligned across channels), but that's another consideration that I hadn't thought of.

Does including RGB as standard place too much of a burden on learners only interested in single channel data, I wonder? And related, can learners go on to apply knowledge of RGB to deal with different types of multi channel data e.g. two infra-red bands? Maybe some more "information boxes" in the initial episodes would be sufficiently helpful?

Just to add that this is also common with scientists who mostly work with electron microscopy, or X-ray microscopy data. There are rarely RGB images.

Some extra 'information boxes' are a good idea. It would be nice to make it clearer how these principles of working with RGB can be extended to any multi-channel data (which is also common e.g. with multi-channel fluorescence microscopy images)

@ivastar I was chatting with @tischi earlier this week and the prospect was raised of a hackathon-like event to try sketching out alternative versions, forked from this lesson and modified to use different central example datasets. We discussed the idea of one version using the kind of microscopy data mentioned by @K-Meech above (@tischi expects to know plenty of people who might contribute to that effort), and a second for the kind of astronomical data you mentioned above.

It sounded like there was some potential for such an event to be hosted in Heidelberg. Does this sound interesting to you?

It sounded like there was some potential for such an event to be hosted in Heidelberg. Does this sound interesting to you?

If I may chime in, I don't live very far from Heidelberg. If you don't have a full team of instructors/helpers yet, I could join perhaps... depending on when you schedule the event (e.g., I'm not available in March).