Issue 040 - Astronomy - Probability and geometry

At what point do satellites make astronomical images hard to avoid?

A new European Southern Observatory study warns that rapid satellite-constellation growth could substantially interfere with ground-based astronomy. There are currently about 15,000 satellites in orbit, while existing proposals could eventually push that number above 1.7 million.

The problem

Estimate the probability that a long-exposure astronomical image is crossed by at least one satellite.

First estimate the probability under roughly today's satellite population, about 15,000 satellites. Then estimate what happens if the number of satellites grows to something like 300,000.

Use the comparison to answer: at what satellite population does avoiding a satellite streak stop being occasional bad luck and become something astronomers should expect in most long exposures?

Because Fermi problems target an order of magnitude, I normally use no more than two significant digits and write most calculations in scientific notation; the Fermi reference explains both conventions.

Before checking sources

Matt's first pass

One of my assumptions must be way off. I assumed the average satellite is orbiting at about 1,000 km above the surface and traveling at about 5,000 m/s. I also assumed a long exposure covers about 1 square cm of sky at about 1 m from the observer and takes about an hour, or about 3,700 seconds.

First, I figured out what distance a satellite would cover during that time:

distance ~= 3.7 x 10^3 s x 5 x 10^3 m/s
         ~= 1.9 x 10^7 m

Then I estimated the total surface area of a sphere at the satellite altitude. Using a radius of about 7.4 x 10^6 m:

satellite-shell area ~= 4 x pi x r^2
                     ~= 12 x (7.4 x 10^6)^2
                     ~= 6.6 x 10^14 m2

Next, I figured out what portion of the sky is covered by a single exposure using a 1 cm square at a distance of 1 m. A 1 m sphere has surface area about 12 m2, so:

fraction of sky ~= 1 x 10^-4 m2 / 12 m2
                ~= 8.3 x 10^-6

search areas in sky ~= 12 / 1 x 10^-4
                    ~= 1.2 x 10^5

A single search area at the satellite shell would therefore cover:

search-area size ~= 6.6 x 10^14 x 8.3 x 10^-6
                 ~= 5.5 x 10^9 m2

search-area width ~= sqrt(5.5 x 10^9)
                  ~= 7 x 10^4 m

Then I tried to figure out how many of these search areas would be crossed by a satellite in an hour. I divided the distance covered in an hour by the search-area width and got about 3 x 10^2 search areas crossed by a single satellite in an hour.

Comparing that to 1.2 x 10^5 total search areas, I estimated about a 0.25% chance that a single satellite would cross a given search area in an hour.

I thought the probabilities could be summed for each additional satellite, so once there are about 400 satellites in orbit, assuming random or even distribution of their orbits, there should be a 100% chance that a satellite crosses a search area in a given hour.

That seems wrong. In reality, satellite orbits will not be perfectly random because launch mechanics creates preferred orbital families. But it seems I must be making an error if it would only take 400 satellites to bring the chance of a streak in one search area up to 100%.

Calibration Score

Matt's Calibration Score: 45 / 100

Higher is better: earn points for accurate pegs, sound models, correct math, and a result close to the sourced answer. The image shows percent full of it: 100 minus the Calibration Score.

Pegs: 10/30. Exposure time, field size, and visible-satellite assumptions were rough but not hopeless.

Model: 15/30. The crossing-rate model was right, but probability needed expected events rather than direct summing.

Math: 0/10. There was a meaningful distance/count arithmetic slip.

Result: 20/30. The broad conclusion about high satellite counts creating persistent streak risk held.

Grounding facts

The full sky is about 4.1 x 10^4 square degrees, and the visible hemisphere is about 2 x 10^4 square degrees. A telescope field of view can be tiny compared with that, but satellites move, so the relevant quantity is the trail area swept during the exposure, not just the instantaneous area of one satellite dot.

The ESO study is also not only about direct streaks. It models satellite positions, motion, brightness, diffuse light from unresolved satellites, and scattered light in the atmosphere. Brightness matters as much as count: one very bright satellite can do more damage than many faint ones.

After checking sources

Check and recalibrate

Matt's model had the right skeleton: satellite streak risk is a crossing-rate problem. The key improvements are to use angular sky motion, a shorter exposure time, and an expected-event probability rather than adding probabilities until they hit 100%.

There was also a small arithmetic slip in the first pass: 1.9 x 10^6 m divided by 7 x 10^4 m is about 27, not 300. Using 1.9 x 10^7 m for an hour at 5 km/s gives about 270. Either way, the larger issue is the probability model.

If the expected number of satellite crossings in one exposure is lambda, then:

P(at least one crossing) ~= 1 - e^-lambda

So lambda = 0.1 means about a 10% chance, lambda = 0.7 means about a 50% chance, lambda = 1 means about a 63% chance, and lambda = 2 means about an 86% chance.

For a check against the ESO study, use its one-million-satellite VLT-style example. The arXiv version describes a 300-second FORS2 exposure at Paranal with an average of more than 8 satellite trails per image at zenith for the one-million-satellite SpaceX scenario. Treat that as:

lambda at 1,000,000 satellites ~= 8 crossings/exposure

If trail rate scales roughly with satellite count, then:

lambda(N) ~= 8 x (N / 1 x 10^6)

For today's roughly 15,000 satellites:

lambda(15,000) ~= 8 x 1.5 x 10^4 / 1 x 10^6
               ~= 1.2 x 10^-1

P(at least one) ~= 1 - e^-0.12
                ~= 1 x 10^-1

That suggests a rough upper-end probability around 10% for a sensitive VLT-style 300-second exposure under conditions where the satellites are illuminated and relevant. The real current probability can be lower because not every satellite is bright enough, sunlit, high enough above the horizon, or crossing the observed field at the right time.

For 300,000 satellites:

lambda(300,000) ~= 8 x 3 x 10^5 / 1 x 10^6
                ~= 2.4

P(at least one) ~= 1 - e^-2.4
                ~= 9 x 10^-1

That puts 300,000 satellites in the territory where streaks are expected in most such exposures. Reuters reports Hainaut's warning that at 300,000 satellites some telescopes could be deprived of most of their data.

The threshold for "more likely than not" happens when lambda is about 0.7:

0.7 ~= 8 x (N / 1 x 10^6)

N ~= 0.7 / 8 x 1 x 10^6
  ~= 9 x 10^4 satellites

A reasonable Fermi answer is therefore that, for sensitive long-exposure imaging during illuminated satellite conditions, the threshold is around 10^5 satellites. That lines up with ESO's broader recommendation that the total population should stay below roughly 100,000 faint satellites if field-of-view losses are to remain comparable to ordinary technical losses.

Post-check reflection

Matt's reflection

Looks like my mental model and assumptions were not terribly far off.

I made a mistake assuming probabilities could be summed, when really the probability approaches 1. This is the second time the suggested peg of expected event probability has come up, and I should really try to understand that better. Correcting that would have pushed the number of satellites necessary before we would expect the crossing event to likely occur upward.

I was way high on the time for a long exposure, more like 5 minutes than 60, and the field width was probably 6 times larger than it should have been, so the probability of a field crossing estimate was high by a factor of about 70.

I also did not exclude satellites for being unlikely to leave light streaks, or factor into my calculations that many are likely to follow a similar path.

But ultimately I think I ended up near the right conclusion: it really does not take tens of thousands of satellites in orbit before there is a risk of streaks in earth-based long exposures, and hundreds of thousands would almost certainly result in multiple unavoidable streaks during exposures.

Recommended memory peg

For crossing and rare-event problems, remember expected events lambda = event rate x exposure time and P(at least one) = 1 - e^-lambda. The useful thresholds are lambda ~= 0.7 for a 50% chance, lambda ~= 1 for a 63% chance, and lambda ~= 2.3 for a 90% chance.

Reader results

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Bars show how submitted estimates sort into the answer choices from the gut-check prompt.

Sources

Reuters: Satellite proliferation imperils astronomical observations, study finds KFGO / Reuters republication: Satellite proliferation imperils astronomical observations ESO: "Beyond the limit": one million satellites and mirrors in space pose grave threat to the night sky O. R. Hainaut: Large or bright satellite constellations Hainaut and Williams 2020: Impact of satellite constellations on astronomical observations with ESO telescopes