Due to the containment measures in place for COVID-19 in Portugal, CreativeMornings Porto events had to move online. Thus making it impossible to do any sort of event photography. This got us thinking how we could replace the empty space on flickr albums. Space is the key word here. The events no longer occur in a shared physical space for all participants but on a virtual one. Nonetheless, there are multiple physical spaces for each participant and these physical spaces are all spread on a larger geographical context. A map then came up as a natural way to capture the physical space of these events.
There would be multiple ways to achieve this, some simpler than others, but since I was doing the job I took it has a challenge to do it with Grasshopper. There are a number of plugins for grasshopper that allow it to import SHP files, work with OpenStreetMaps, or GoogleMaps, for instance Heron, Elk, Meerkat or Mosquito, besides Grasshoppers default Import SHP. For this I decided to use Mosquito to import the Maps from OpenStreetMaps, Heron to get the Lat/Lon coordinates from addresses. Mosquito also has a component that returns coordinates from street addresses but it is not as effective in dealing with a large amount of addresses. Also, one of the initial ideas was to use the geotags in the images’ metadata but they arrived without any geographical information.
Each participant was asked to provide two pictures with the address from where they were participating in the CM event. I was sent the images named with the following format: FirstName LastName_Borough_City.jpg. To display the images of each participant at its geographic location I used Human plugin to map the images to surfaces. Lastly, since the participant addresses were only discriminated to borough (freguesia) level there were a few overlapping participants on the map. Two solve this I used Kangaroo to optimize the placement of each frame, as close as possible to the original point with as little overlap as possible.
One unforeseen hurdle was that there were many participants outside Porto’s metropolitan area. Mosquito is not ideal to deal with national level data since it always requests major roads from OpenStreetMaps. The problem is that at large scales it can quickly turn into large amounts of data to fetch from the internet, making the script sluggish to work on. A makeshift solution was to import a SHP file with the national borders, which can be found here, and scale the national border and the point locations down to fit in a smaller area next to the city level map.