Gralhix OSINT Excercise #002
When I opened Gralhix’s OSINT Exercise 002, I immediately felt at home, even though I’ve never been to this specific location or part of the world. The scene was unmistakably urban — a transit station with a train waiting at the platform and tall buildings rising in the background.
Having lived much of my life in cities, I’m very familiar with this kind of setting. Public transportation is second nature to me. Countless hours waiting on platforms, riding trains and buses, watching the sea of humanity that passes through transit hubs each day.
The details were new, but the vibe was recognizable. And that’s often the key to geolocation challenges like this — finding the common patterns and tells hidden in the unfamiliar. With that mindset, I went to work beginning with the same methodology we used for the Kiffa challenge.
Context, Foreground, Background & Map Markings
Breaking down an image into these key components is a crucial first step in any geolocation challenge. It allows us to systematically catalog the visible clues and establish a framework for the investigation. So let’s dive in:
- Context: none provided. We’re left to rely solely on the visual details to orient ourselves.
- Foreground
– Commuter rail platform with partial roofing above the photographer, likely to shield waiting passengers from the elements
– Numerous tall green weeds close to the photographer and trees behind the train suggest spring or summer
– Handful of passengers dressed for pleasant or warm weather waiting on benches or boarding train
– A train silver in color with blue accents, the engine has yellow markings on the face and “metro” painted on the side
– Overhead wires suggest electric trains
– Three station platforms visible - Background
– Tall spire and six buildings visible
– Second building from the left has a sign “HWT”
– Building next to it: “IBM”
– Smaller building in front of IBM has a stylized “L” visible - Map Markings
– Multiple signs reading “Flinders Street”
As you can see, this structured approach ensures we don’t overlook any potential leads. The foreground elements help narrow down the time of year and type of transit system. The background buildings, especially those with visible signage, offer valuable reference points for pinpointing the location. And of course, the “Flinders Street” signs are a dead giveaway for the station’s name, which brings us to our tasks for this challenge:
a) What is the name of the train station seen in the photo?
b) What is the name and height of the tallest structure seen in the photo?
The “Flinders Street” signs are indeed the key to answering the first question. However, before we celebrate and call it a day, we need to confirm that this is a unique station name. After all, there could be multiple Flinders Street stations across the country or even the world.
To check this, we could manually search for “Flinders Street Station” in various cities and see if any match the photo. But that would be tedious and time-consuming. Instead, let’s work smarter, not harder, and enlist the help of Google Image Search.
Click search and……voila!
The reverse image search has indeed hit pay dirt. The top result confirms that our mystery location is Flinders Street Railway Station in Melbourne, Australia. Scrolling through the other matches, we see the same distinctive station facade, platform, and trains from various angles and times of day. Even the background buildings line up perfectly. There’s no doubt about it — this is the one and only Flinders Street station we were looking for.
With that crucial piece of the puzzle in place, we can confidently check off the first question and move on to tackling the second: identifying the tallest structure visible in the original image. Now that we know we’re in the heart of Melbourne, we can pivot our search on the city’s notable high-rises and landmarks to see which one matches that striking spire.
With the buildings clearly labeled, we can now cross-reference them with a recent satellite view of the area using Google Earth Pro.
By comparing the satellite imagery with the original photo, I’ve pinpointed the photographer’s location to 37°49'6.11"S 144°57'58.44"E. The Flinders Station station platforms, the distinctive tree line, and the positions of the tall buildings line up perfectly, confirming we’re looking at the same spot.
For further validation, let’s turn to a 2014 Google Street View image taken near the Arbory Bar and Eatery, just below the station platforms:
This street-level perspective provides a clear view of the same buildings and spire, albeit from a slightly different angle. The fact that two of the structures are missing in this 2014 image but are present in the more recent photo helps establish a timeline for the construction in this area.
So, what structure is the tallest?
hile looking up the height of a half dozen or so buildings isn’t the most laborious of tasks, I wasn’t keen on googling each one individually. Instead, I saw this as an opportunity to showcase the power of OpenStreetMap (OSM) and Overpass Turbo for OSINT investigations.
For those unfamiliar, OpenStreetMap is a free, editable map of the world, created and maintained by a global community of volunteers. It’s essentially the Wikipedia of maps, with an extensive database of geospatial information that often includes details not found in commercial mapping platforms.
Overpass Turbo is a web-based tool that allows you to query and extract data from OSM using a specialized API language. It’s an incredibly powerful tool for OSINT researchers, enabling them to quickly find and filter relevant geospatial information without manual searches.
To identify the tallest structure in the image, I crafted the following Overpass Turbo query to fetch any structures tagged with a height value greater than 100 meters:
[out:json][timeout:25];
{{geocodeArea:Melbourne}}->.searchArea;
(
way(if:t["height"] > 100)
(area.searchArea);
relation(if:t["height"] > 100)
(area.searchArea);
);
out body;
>;
out skel qt;
// To search for different heights change both numbers after the > sign 
The query returns a handful of results, which can be easily exported into a table from the data tab in Overpass Turbo. Here’s the relevant data, sorted by height:
Number Name Height in Meters
5 Focus Melbourne 166
1 Art Centre Spire 162
4 IBM Tower 132
3 HWT Tower 111
6 Langham Hotel 81
2 Qway West 78It’s worth noting that the query results do include a few false positives — structures that don’t meet the 100-meter threshold. This is likely due to inconsistencies or errors in the underlying OSM data rather than a fault in the query itself. However, for our purposes, the key information is still clear.
To confirm the accuracy of these figures, I cross-referenced them with the Council on Tall Buildings and Urban Habitat database and the City of Melbourne’s OpenData site for 2023 Building Footprints. Both sources corroborate that Focus Melbourne, standing at an impressive 166 meters, is indeed the tallest structure visible in Gralhix’s OSINT Challenge #002.
This investigation showcases the importance of a multi-faceted approach to geolocation challenges. By first examining the context, background, foreground, and any visible map markings, we were able to narrow down the location using Google Earth Pro and Google Street View. Then, to answer the question of the tallest structure, we turned to the wealth of open-source geospatial data in OpenStreetMap, using an Overpass Turbo query to quickly extract the relevant information.
While Google’s tools are indispensable for OSINT work, this case study demonstrates the value of augmenting them with other open-source resources like OSM. By leveraging the unique strengths of each platform and cross-referencing the results, we can build a more comprehensive and accurate picture to solve even the most challenging geolocation puzzles.
