Hey everyone!
I’m forming a team for a citizen science project called IASC — International Astronomical Search Collaboration and I’m looking for teammates! Interested?
It’s nothing too crazy and the process can be underwhelming. I’ll say that just so you don’t expect anything extraordinary.
Basically, what we’d have to do is analyse images that will be sent to us from these two observatories in Hawaii called Pan-STARRS 1 and 2. And we’d have to look for moving possibily unidentified objects and send an report to IASC (the organization behind it).
It’s super quick and simple, and it really shouldn’t take more than 20 minutes per pack out of your day and you’ll have an entire month to sort through the packs. So, time really isn’t an issue and you can do things on your own time.
This is a great way to be part of hands-on science. You’re helping scientists track objects and identify new ones. This is very relevant, especially on a planetary defense level. You can’t protect yourself from a threat you don’t see coming.
They offer certificates to all participants, and the certificates are pretty neat.
Requirements/preferences:
- Willing to commit some time to analyzing telescope images
- Preferably located in the Americas, Europe, or Africa (similar time zones are a plus)
Relevant links: https://science.nasa.gov/citizen-science/international-astronomical-search-collaboration/ http://iasc.cosmosearch.org/
If you want in or have questions, lmk below :)
(Sorry if this isn’t allowed mods. I couldn’t find anything that said I couldn’t do this in the rules T-T)
Love it. However, I feel that it should be possible to automate the procedure: Grab images, sort them, and compare them to find any moving objects. Then somehow look them up to check whether it’s already registered.
Sounds like a reasonably simple script wrapped around curl, some gfx library calls, and possibly selenium or WWW::Mechanize
Automated software has a threshold for signal-to-noise ratio to avoid false positives. Human eyes (us hunters) are much better at spotting faint moving objects that dip below the threshold of the automated pipelines! :)
I have a feeling that this human step might be at the end of a chain of automated filters.