Simple GPX Tile Hunt - Identify undiscovered areas

Fig: Map showing the visited areas in blue — each 1.5 km² (configurable) in size — at various zoom levels

• Why:
  • Statshunters.com, squadrats.com, ... require payed and maintained Strava account
  • so, I built something simple of my own (80/20)
• Requires:
  • Linux
  • Python 3 with pip (usually pre-installed)
• Usage:

   $ ./setup.sh     # Installs libs to the project's subdir 'local', so your system stays clean
   $ ./gpx2kml.py   # Creates tile mesh KML-file from ./routes/*.gpx ; see --help too
   $ ./kml2htm.py   # Creates a local tile mesh viewer from KML-file and OpenStreetMap

• Input:
  • Komoot.com users: download recorded tours to the routes directory
• Viewers:
  • Web-browser and local HTML-file generated by kml2htm.py
  • Google My Maps: Create a map, create new layer, import generated KML-file
• Pro & Cons:
  • ...
• Alternative:
  • Komoot.com: create a collection and add all existing tours to it, then examine the collection's map. Might be sluggish and perhaps be limited by tours, it's less clear than the tiles grid
  • Pay and maintain a Strava account (synchronize tours data)
  • ...

See Also

• my stared cycling tools on GitHub: https://github.com/stars/andre-st/lists/cycling
• untested: more elaborate https://github.com/mouton0815/view-every-tile (Node.js)