Mobility Tracking in Hamburg

Mobility Tracking in Hamburg/Germany based on geotagged photo data for Hamburg and surroundings published on flickr from 2003 to 2012. Animation cycles through the time of day when pictures where taken: morning (orange), day (yellow), evening (purple), night (blue).

One-sentence Synopsis:

Georeferenced photo data taken from flickr for Hamburg and surroundings shows highly frequented hot spots and (maybe more interesting) “blank areas” in a 1.7 million city.

Data source:

Data has been scraped from flickr using automated API calls.


Data has been converted from XML to CSV format by a bash script. Hot spots have been normalized by only including one data point per user and location (this mainly applies to “Volksparkstadion” and “Miniatur Wunderland”, where a few users have published dozen and hundreds of pictures). The map was created with CartoDB. For more details see this interactive but static map.

Key figures:

  • total of 120,000+ data points
  • time frame: from 2003 to 2012


This finger exercise was obviously inspired by Eric Fischer’s series of maps See something or say something.

“Well, at the most fundamental level, a tweet or a photo with a location signifies someone’s presence at a particular place at a particular time, and the presence of people in itself is indicative of the significance and interest of a place. And a picture goes further, saying that not only was someone there, they also saw something interesting enough to bother photographing and sharing.” (Eric Fischer)


  1. Matt Curcio says:

    I ran across your “Mobility Tracking in Hamburg” web page and thought it was very interesting. GREAT STUFF! I was interested to learn if you used R or python for the work. Do you have a github site?

    • marianoju says:

      Hej Matt, thanks for your comment! No python was harmed in the making of this post. I see you found out my incognito github handle, but you will have noticed I haven’t published any code there (yet). Sorry for that!

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