Pinpointing Russian Troop Locations in Ukraine Using Open Source Intelligence
On August 28, 2014 NATO released a series of satellite images showing Russian troops operating inside the sovereign borders of Ukraine. These images are black and white photos without any specific location details (i.e. no latitude and longitude information was provided).
The team at SigActs decided to use one of the photos to pinpoint the actual location of a Russian self-propelled artillery column. Using the satellite image snapped on August 21, 2014 and some imagery analysis methods we were able to georeference and accurately overlay the NATO slide onto a Google Maps satellite imagery layer.
With this photo “georeferenced” and accessible as a map layer, we can visualize the Russian troop locations in a much more complete context. The Russian troops pictured in the NATO slide are well inside of Ukraine, over 7 miles from the nearest stretch of the Russian border (geographic coordinates: 48.366414, 39.6966667).
In the satellite photo the Russian column is heading West out of Sukhodilsk on a rural road. The town of Sukhodilsk is in the Luhansk Oblast province of Ukraine. According to a 2001 Ukrainian census, 92% of the population in the area around Sukhodilsk is Russian.
Coal mining is the predominant industry in the area around Sukhodilsk, and the water feature just West of the Russian column location is actually a tailing pond from the nearby coal mines. North of the water feature is a damn owned by a Russian company called Moscow JSC (registered in Moscow as “Donetsk Machinostroitel”).
With this additional context, it is reasonable to assume that the Russian self-propelled artillery column depicted in the satellite image is operating in an area with a very pro-Russian population and amidst a local economy heavily tied to Moscow.
At SigActs we pride ourselves in adding context to news reporting by unlocking geospatial relevance. When information is visualized on a map it can reveal connections, patterns and trends that might otherwise be missed. We would love to help you visualize where news may have relevance to the places on the Earth that are important to you, your customers and your business!