Gralhix OSINT Exercise #009
Efficient Geolocation with Overpass Turbo
The Bike Path That Wasn’t Just a Bike Path
Sometimes, the most interesting OSINT challenges come from the most mundane sources. Take, for instance, a simple video of people walking on a bike path. Sounds boring, right? But when that video is part of an OSINT exercise, it suddenly becomes a puzzle waiting to be solved.
Here’s the challenge Gralhix threw at us:
- Figure out when the video was recorded.
- Pinpoint where the person was walking.
If you’re new to OSINT, you might be scratching your head, wondering how anyone could extract precise location and time data from a simple video of a bike path. Even seasoned investigators might pause for a moment, mentally flipping through their toolkit of techniques. Gralhix, who crafted this challenge, rated it as hard for beginners and medium for experts. But here’s the thing: with the right approach, even seemingly difficult tasks can become manageable, sometimes even enjoyable. Let me walk you through how I tackled this one.
When I first watched the video, I felt a little surge of excitement. Not because I’m particularly thrilled by bike paths (though as a cyclist, I do appreciate a good one), but because I immediately recognized this as a perfect candidate for an Overpass Turbo query. It’s a tool I’ve been learning, and I was eager to put it to the test.
The video itself is pretty straightforward: 24 seconds of someone walking on a shared pedestrian and bike path in Tirana, Albania. But in those 24 seconds, there’s a wealth of information if you know what to look for.
First, the path itself. It’s not your average bike lane. This one runs right down the middle of a major road, separating two lanes of traffic on each side. It’s the kind of thing that makes urban cyclists drool and city planners argue. More importantly for us, it’s distinctive. Unique features are gold in geolocation work.
Then there’s the big building looming in the distance, and, after a few seconds, a pharmacy with its telltale glowing cross. These might seem like minor details, but in OSINT, there’s no such thing as a minor detail.
The sun’s setting straight ahead, which tells us the road runs east-west. That’s a useful tidbit for narrowing down our search. Now, here’s where a bit of healthy skepticism comes in handy: The tweet claims this video was taken in February, but in OSINT, we don’t take anything at face value. So I looked closer. People are wearing jackets and long sleeves. It’s not proof positive, but it does suggest a cooler temperature that doesn’t contradict the February claim. It’s a small detail, but these little confirmations can add up. As investigators/researchers, we’re always looking for these soft verifications — little clues that either support or challenge the information we’re given.
All of this — the unique bike path, the tall building, the pharmacy, the sunset — they’re not just scenery. They’re data points. And data points are what make OSINT work.
Now, we could start combing through Google Earth, looking at every east-west road in Tirana. That’s one way to do it. It’s also a great way to waste an afternoon. Instead, let’s see if we can work smarter, not harder.
This is where Overpass Turbo comes in. It’s a query language for OpenStreetMap, and it’s about to save us a lot of time.
The Power of a Good Query
Here’s the thing about Overpass Turbo: it’s like having a superpower, but one that takes some practice to control. It lets you ask OpenStreetMap very specific questions. In this case, we’re essentially asking, “Hey, show me all the places in Tirana where there’s a tall building near a bike path and a pharmacy.”
Here’s what that looks like in query-speak:
[out:json][timeout:25];
{{geocodeArea:Tirane}}->.searchArea;
// Get bike lanes
(
way["highway"="cycleway"](area.searchArea);
way["bicycle"="designated"](area.searchArea);
way["cycleway"](area.searchArea);
)->.bikelanes;
// Get pharmacies
(
node["amenity"="pharmacy"](area.searchArea);
way["amenity"="pharmacy"](area.searchArea);
)->.pharmacies;
// Get tall buildings near bike lanes and pharmacies
(
way(if:t["height"] > 50)
(around.bikelanes:25)
(around.pharmacies:100)
(area.searchArea);
relation(if:t["height"] > 50)
(around.bikelanes:25)
(around.pharmacies:100)
(area.searchArea);
);
out body;
>;
out skel qt;I know, it looks like a cat walked across my keyboard. But trust me, this gibberish is powerful. It’s looking for buildings over 50 meters tall, within 25 meters of a bike lane and 100 meters of a pharmacy. Why those numbers? Educated guesses based on the video. OSINT is part science, part art.
When we run this query, something magical happens. Instead of having to search all of Tirana, we’re left with just a handful (just four!) of possible locations. One of them, on an east-west road, looks promising.
From Query to Street View
And there it is. The bike path, the tall building, the pharmacy with its glowing cross. It’s like seeing an old friend in a crowd. Except this friend is a very specific stretch of road in Tirana, Albania.
First, there’s our towering friend, the Tirana Garden Building (#1). It’s hard to miss, standing tall and proud in both our Street View and our satellite image. This isn’t just any tall building; it’s a landmark with vivid features that help anchor our location.
Next, let’s look for our pharmaceutical beacon (#2). Remember that glowing cross we spotted in the video? There it is in Street View, right where we expected it to be. It’s like finding the second piece of a puzzle — satisfying and reassuring.
But here’s where it gets interesting. Remember that white sign with blue letters we noticed in the video? Street View gives us a closer look, revealing it as a Fibank branch (#3). This wasn’t part of our original search criteria, but it’s a golden nugget of confirmation. It’s these unexpected corroborations that often seal the deal in OSINT work.
To drive the point home, I’ve prepared a side-by-side comparison. On the left, we have our annotated OpenStreetMap view. On the right, the same area overlaid in Google Earth Pro. See how our key elements line up perfectly? The unique bike path (highlighted in light blue), our tall building, the pharmacy on left, and even the bank — they’re all exactly where they should be.
This multi-source verification is the backbone of solid OSINT work. We’re not just relying on one map or one image. We’re cross-referencing across platforms, each confirmation building our confidence. It’s like having multiple witnesses all telling the same story — it’s hard to argue with that kind of consensus.
In OSINT, we’re always piecing together a puzzle. Sometimes we start with the edge pieces — like our distinctive bike path. Other times, we get lucky with a centerpiece — like our tall building. But it’s these smaller details, the pharmacy, the bank sign, that often fill in the crucial gaps and lock everything into place.
Putting it all Together
Google Earth Pro gives us the coordinates for the walk’s path:
- 41.3269, 19.8073 for the start
- 41.3267, 19.8067 for the end.
Telling Time by the Sun
Now, here’s where things get interesting — and where I have to eat a slice of humble pie. Initially, I thought we were looking at a sunset. Logical, right? The tweet said “Sunset in Tirana,” so case closed. But something kept nagging at me.
It wasn’t until I was elbow-deep in dish soap that it hit me: if the sun had set, why wasn’t it darker? Sometimes, the best OSINT insights come when you’re not actively working on the problem. It’s a reminder that our brains keep churning even when we think we’ve moved on.
Here’s what I realized: this video isn’t capturing the sunset itself, but rather that magical moment just before. Photographers call it the “golden hour” for a reason. It’s when the sun aligns perfectly with major streets or landmarks, creating those postcard-perfect shots. You’ve probably seen similar images from Manhattan’s “Manhattanhenge” or England’s Stonehenge. Turns out, Tirana has its own version of this phenomenon.
Take a closer look at the video. See that extra bright spot just behind the trees on the right side of the street? That’s our sun, getting ready for its grand exit.
So, how do we pin down the exact time? This is where our friend Suncalc shines (pun absolutely intended). We input the date from the tweet (February 16, 2023) and the coordinates we geolocated for the start of the video (41.3269, 19.8073). What we get is a super helpful l visualization of the sun’s journey on that day.
Let me break this down for you:
- The arm on the right shows where sunrise would have been.
- The left arm indicates sunset.
- That yellow arm in the middle? That’s our time machine. We can move it using the slider at the top of the screen.
Here’s the magic: when we align that yellow arm with Rruga e Kavajës (our street with the unique bike path), we get our answer. The video was taken at approximately 16:47 UTC+1.
This whole process taught me two valuable lessons in OSINT:
- Always question your assumptions. Even when something seems obvious (like a “sunset” tweet actually being at sunset), dig deeper.
- Sometimes, stepping away from a problem is the best way to solve it. My dish-washing epiphany proves that your subconscious can be your best OSINT partner.
Remember, in OSINT work, being wrong isn’t a failure — it’s an opportunity to learn and improve. The real failure would be sticking to an incorrect conclusion in the face of contradicting evidence. So next time you’re stuck on a problem, maybe do some dishes. You never know what insights might bubble up.
What We Learned
This exercise was a masterclass in the power of combining tools. Overpass Turbo narrowed our search dramatically. Google Street View and Earth Pro confirmed our findings. Suncalc pinpointed the time.
But more than that, it showed the value of paying attention to details. The unique bike path layout, the tall building, the pharmacy — each of these elements might seem insignificant on its own. Together, they created a digital fingerprint that led us straight to our answer.
It also reinforced something I’ve learned time and again in OSINT work: your weird hobbies and random knowledge can be invaluable. My interest in cycling made that bike path layout stand out. Countless hours playing the 4x game Civilization 6 reminded me of Stonehenge. and building reminded me of Never underestimate the power of your unique perspective.
The Road Ahead
OSINT is a journey, not a destination. Each exercise teaches us something new, honing our skills a little more. This one taught me the power of combining multiple criteria in an Overpass Turbo query. It’s a technique I’ll definitely be using again.
For those just starting out, don’t be intimidated by the technical aspects. Yes, that Overpass Turbo query looks daunting. But remember, I started where you are. The OSINT community is incredibly supportive, and there are tutorials for every tool you can imagine. Take it one step at a time, and before you know it, you’ll be crafting queries of your own.
And for the veterans out there, I’m curious: how would you have approached this? Have you used Overpass Turbo in your work? What other creative tool combinations have you found effective in geolocation tasks?
OSINT is a collective endeavor. We learn from each other, build on each other’s techniques. So let’s keep the conversation going. Who knows? Your insight might be the key to cracking the next challenge.
A Tip of the Hat
A big thanks to Gralhix for crafting this exercise. If you’re hungry for more OSINT challenges (and trust me, once you start, it’s hard to stop), check out her website at https://gralhix.com
And for those looking to dive deeper into the tools we used:
- Suncalc: https://www.suncalc.org/
- Overpass Turbo: https://overpass-turbo.eu/
- Overpass Turbo Wiki: https://wiki.openstreetmap.org/wiki/Overpass_turbo
- Overpass Turbo API: https://wiki.openstreetmap.org/wiki/Overpass_API
And for a video tutorial to get started with Overpass Turbo, you’ll be well served by soaking in knowledge from OSINT professional Benjamin Strick:
Remember, in OSINT, every new tool in your belt is another key to unlocking the world’s mysteries. So keep learning, keep exploring, and most importantly, keep sharing what you discover. After all, that’s what makes our community so powerful.
