Quick Answer: Yes. YouTuber and researcher Colsto has shown that faint aircraft sounds in a video's background can be used to estimate where the recording was made, reportedly to within 100 meters. The method uses Doppler shift measurements from a spectrogram, matched against public flight data. Video geolocation from audio works even when no plane is visible on screen.
A plane you can't hear might still be on your recording. That's the core of a technique that TechRadar's Carrie Marshall covered after Colsto's viral video. Colsto says roughly 60 seconds of audio can be enough. The sound doesn't need to be loud enough for a human listener to notice. If you publish video or audio, or you're trying to protect your location, you should understand how this works and where it breaks down.
How the Doppler Effect Turns Engine Noise Into a Location Clue
The Doppler effect is the change in perceived frequency when a sound source moves relative to a listener. You hear it when an ambulance passes you: the pitch drops as it moves away. Aircraft produce the same effect. Their engines and propellers emit tones, and as the plane flies past a microphone, those tones rise and then fall in a predictable curve.
Here's the key shift in thinking. Most people treat a faint plane as noise to be cleaned away. Colsto treats it as a signal. On a spectrogram, a visual map of frequency over time, a passing aircraft shows up as a curved line with harmonics stacked above it. The shape of that curve depends on the plane's speed, altitude, and its closest point of approach to the microphone.
When you know the aircraft's path and speed, you can work backwards. The curve tells you how far the plane was from the recorder at each moment. Repeat that with a second aircraft, and the intersection of the two distance estimates narrows the recorder's location. That's triangulation, and it's why multiple planes make the result more precise.
Where the Data Comes From
The flight side of the technique relies on public data. Most commercial aircraft broadcast their position through ADS-B (Automatic Dependent Surveillance–Broadcast), a surveillance standard that the US Federal Aviation Administration requires for most controlled airspace. Community networks such as the OpenSky Network collect these broadcasts and make historical data available to researchers.
Combine that with a spectrogram analysis tool and some careful math, and you have what the OSINT community calls a workflow. OSINT (open-source intelligence) means building conclusions from publicly available material. Colsto's point is that the audio itself is the raw material, and the flight records are the reference map.
Colsto has been clear that the video is educational. The explanation covers the aircraft data used, how the Doppler measurements were filtered, and what corrections were applied. It doesn't include ready-made software. That matters, because the gap between understanding a method and running it reliably is large.
Why Standard Audio Cleaning Doesn't Solve It
This is the counter-intuitive part, and it's where most people's instincts fail. The popular advice is to run a high-pass filter or a noise reduction pass to erase distant sounds. In practice, that often doesn't remove the aircraft signal.
The reason is frequency overlap. A high-pass filter cuts low frequencies, but aircraft tones and their harmonics can sit in the same band as voices, room tone, and wind noise. Noise reduction algorithms look for steady background sounds and suppress them. A moving aircraft's tones change over time, so an aggressive pass can smear or delete the very curve you're trying to hide, or leave enough of it behind to analyze. You can't assume that filtering makes the signal disappear. It may just make it harder to notice.
This doesn't mean cleanup is pointless. It means you need to think about the signal the way an analyst would. Ask whether the aircraft's frequency trajectory is still there in a spectrogram after you've processed the audio.
How Serious Is the Risk?
Colsto argues the odds are low. In a quote reported by TechRadar, he said: "The odds that someone can and does actually do this is pretty slim. In reality, there's probably a hundred easier ways to find you than this." That's a fair point. Most people who record video have far more obvious exposure: visible street signs, uploaded metadata, reflections in windows, or distinctive landmarks.
The risk rises in specific cases. Colsto's demonstration used audio from a security camera, and he noted that the same method could apply to "footage from a investigation or a video online." A video with no visual clues could still be placed if it has a steady aircraft soundtrack and a reasonably accurate flight record for the area.
It's also worth being honest about the limits. The "within 100 meters" figure is the claim reported by TechRadar and presented in the video. It depends on good audio, known flight paths, and a region with enough traffic to triangulate. A quiet rural recording with one distant plane is a much weaker case. Treat the accuracy figure as the best-case result, not a guarantee.
| Scenario | Aircraft audio present? | Likely outcome | Main factor |
|---|---|---|---|
| Busy metro area, indoor recording | Often yes, faint | Location narrowing possible | Number of flights overhead |
| Security camera in an airport corridor | Yes, strong | Strong candidate for analysis | Clear engine tones |
| Rural outdoor recording, one distant plane | Weak | Low confidence | Only one aircraft to triangulate |
| Vlog with music and speech mixed in | Masked | Hard to analyze | Overlap with other sounds |
What You Can Do Before You Publish
Here's where it gets practical. You're not going to remove every trace, but you can reduce the risk.
- Check the soundtrack, not just the picture. Listen for steady hums, distant engines, or propeller tones. If you hear them, a spectrogram can likely show them too.
- Record away from flight paths when location matters. Moving a few hundred meters from a flight corridor can change the signal you pick up.
- Replace the original audio when privacy matters. Swap in a clean music bed or a re-recorded voiceover. This removes the aircraft signal entirely rather than trying to filter it.
- Strip metadata from files. Location tags in EXIF or container metadata are a far easier clue than any audio analysis.
- Test your own output. Open the file in a spectrogram viewer and look for curved harmonics before you upload.
These steps work because they remove the signal at the source. Trying to fix it afterwards is the weaker path.
The Bigger Pattern Behind Ambient Signals
This story is part of a wider pattern. TechRadar has also covered Wi-Fi routers that can help locate people indoors, and Wi-Fi sensing that can track movement without a connected phone. The common thread is that ambient signals carry more information than we expect. A recording, a radio wave, or a router signal can reveal something about where its source is, even when the source isn't obviously exposed.
That's why the useful question isn't "Can this happen?" but "What background signals am I leaving in my recordings and devices?" For most people, the practical answer is small: a few audio habits and metadata settings. For journalists, researchers, and anyone documenting sensitive locations, the bar is higher and the checks should be routine.
Frequently Asked Questions
What is video geolocation from audio?
Video geolocation from audio is the process of estimating where a recording was made by analyzing its sounds. In the Colsto method, faint aircraft engine tones shift in frequency as planes pass, creating a Doppler curve. That curve is matched against public flight data to narrow the recorder's position, reportedly to within 100 meters.
How can I stop my video from revealing my location through sound?
Replace the original audio with a clean track, or record in a location away from flight corridors. Filtering alone can fail, because aircraft tones overlap with speech and room noise. Removing the metadata and checking your audio in a spectrogram viewer before publishing also reduces your exposure.
Why doesn't a high-pass filter remove aircraft noise?
Aircraft tones and their harmonics often fall in the same frequency range as voices and background noise. A high-pass filter can cut low frequencies but may leave the aircraft's curved trajectory intact. Noise reduction can also smear the signal instead of deleting it, which can make analysis harder but not impossible.
Can someone geolocate a video that has no visible clues?
Yes, in principle. Colsto has said that footage with "literally zero visual clues" could be located if it has usable aircraft audio and a region with enough flight traffic. Accuracy depends on audio quality, the number of planes, and the availability of accurate flight records.
Protect Your Location Before Your Next Upload
The most actionable takeaway is simple: listen to your recording the way an analyst would, and treat any steady aircraft tone as a location clue. Before your next upload, play the audio back, check for engine or propeller hum, and swap in a clean soundtrack if you find one. Then pass this to a colleague or friend who records outdoors, especially anyone whose videos could reveal a home or workplace.