For people doing photometry: how much do satellite trails actually matter in practice?

Community General Discussion
1

Hello everyone,

I’m trying to learn more about how satellite trails affect measurement-focused observing, especially photometry.

A lot of the discussion I’ve seen online comes from general imaging or astrophotography, where people often talk about stacking, rejection, or removing trails in post-processing. But I’m more interested in the practical side for people who care about the measurements themselves.

For those of you doing photometry, I’d really like to know:

  • When do satellite trails become a real problem in your workflow?
  • Is the main issue loss of usable data, extra rejection/QA work, reduced precision, or something else?
  • Does it depend a lot on target type, field size, cadence, or observing setup?
  • Are there tools or habits you already use that make the problem mostly manageable?

I’m asking because papers often say satellite contamination is a serious issue for astronomy, but I’m trying to understand what that means in actual observing practice for photometry users.

Thanks very much — any real workflow examples would be very helpful.

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In my experience, unless the satellite trail is unusually bright, they affect the photometry only when the trail comes close to the variable or the comparison/check stars. That is, when the trail would be included in the measurement aperture or the background apertures of the stars.

I have been using the free ASTAP software which has a very helpful streak detection function to automatically inspect each of my images. It works very well as it detects even the faintest satellite trails. When it detects a trail, I go back and visually inspect those images and determine if the trail might distort the photometry.

Of course if you see something that looks amiss in the photometry itself, you should always go back and double check the images themselves and your measurement process.

…Tim

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