Updated September 2025
I’ve always thought it would be a fun ‘side quest’ in life to walk every street, trail, and park on the planet. So for the past decade I’ve made it my mission to do that. I want to see everything. Sure, maybe walking 100 million miles is impossible in a human lifetime, but why not try? Worst case, I have a lifetime of adventures exploring every corner of the world.
Since starting this mission in 2015, I’ve GPS-tracked 50,000 miles of walking in over 200 cities and dozens of countries, averaging 10-20 miles per day, which keeps me so healthy I’m functionally immortal (I’ll write another post on this). This project will permanently be a work-in-progress.
To log the data, rather than opening a tracking app every time I go for a walk, I have my phone configured to track me 24/7 in the background. This means I capture everything, every second of every day. I’m confident I’m the first person ever to track their life like this at this level.
I often get asked how to do this. No all-in-one app exists for this, so it’s extremely difficult. If you’re committed, here’s the system I use, however if you want to stay sane I highly recommend just using a fitness tracker like Strava synced to a tool like Citystrides or Wandrer.
- Install Arc (and maybe Arc Mini and Arc Recorder for backup) on your iPhone. The apps have a ML model that cleans and classifies the data. Occasionally you’ll have to manually classify data the model can’t sort out.
- Export the data in JSON format and use a Python script to parse it and strip out everything except walking. You can visualize the JSON data on this website.
- Finally, use Python scripts to consolidate everything, convert the data to GeoJSON, downsample it to reduce the file size, and upload it to Mapbox via their API as a dataset. Then it’s easy to convert the data to a tileset and visualize everything on a custom map.
Here’s an interactive map in which you can explore the data. Note: like everything, this is currently a work in progress; Mapbox downsamples the data which makes the map jagged at deep zoom levels, I need to learn how to code it to visualize the accurate raw data. I also redacted a few residential addresses, and there’s still some data from 2015-2019 I need to upload, as well as recent data. Otherwise, this is everywhere I’ve walked in the past 10 years!
The data is color-coded by year, with two exceptions: purple represents multiple years (2015-2019) and orange is Strava data, which I more recently have been using as a backup on long walks.
It’s neat to see how GPS inaccuracies emphasize the streets I walk most often, and how the neighborhoods I walk often have changed over time. At the same time, GPS is accurate enough to track my movement within large buildings such as the Met or IKEA. Fun fact: this is an example of a four-dimensional map.
I frequently get asked how different this map would look if I didn’t have my mission to walk every street. The answer is very different; humans naturally tend towards taking familiar routes, so a ‘normal’ map would just be straight lines between your most frequent destinations. That is why I’m the first person ever to do this: some people track their walking like this, and some people walk every street, however, I’m the first person ever to do both!
New York City is my favorite city in the world and thus has the most data – since July 2015 I’ve walked about 20,000 miles here. I’m on track to finish every street in Manhattan very soon.
Feel free to pan over to other cities on the map. For example, San Francisco, where I’ve walked around 7,000 miles (75% completion), or Mexico City, where I’ve walked about 2,500 miles (5% completion). Oaxaca and Los Angeles also look decent.
I have more more writing to add to this post soon!
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