To do this, you need to know the correct OpenStreetMap tag to query. You can search for those objects by adding a custom filter in the tool. There might be some features in an image that don’t yet have presets in our tool. Without “railroad,” it is more difficult, but can be matched using pedestrian paths or buildings. For example, “plaza/square,” “water body,” and “railroad” find it quite easily. “Plaza/square” and “water body” could also be useful search queries for this location.
Since we now know the area we are looking at, it is possible to experiment with filters by zooming in on Brussels and searching only that region. Making the search more general means that some queries might time out. Reversing “shop (any)” and “fountain” so that “fountain” is the first filter in the query will instead return one result for each fountain. Also notice that it includes many very similar locations, because it will return one result for each shop, as this is the first item in the query. However, the correct location is still included. The simplest modification is to select “shop (any)” instead of “convenience store” combined with “fountain” and “railroad.” Notice that this returns many more results, because it is a more general query. On the OpenStreetMap web interface, the “query” tool can be used to view information about the features that exist in the map and how they are tagged. Bellingcat’s tool is set up to search the database from April 2023 and will be updated twice a year. Additionally, OpenStreetMap is only as current as its last user-submitted edit, so certain features may not be up-to-date. For example, you might see a tree in your image, but every individual tree is unlikely to be mapped. It can take some experience, intuition and guesswork to choose which features to include in your search query. It is also possible to export the results as a CSV or a KML file that can be opened in Google Earth. The user can toggle between OpenStreetMap, Google Maps, Google Terrain, or Satellite imagery using the toggle above the results. Success! There’s no water in the fountain in the Google Street View image, and the corner store has a different name, but the intersection is clearly the same.įor some queries, it might not be immediately obvious from the map chips which result is the best.
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