At the beginning of this year I wrote a post about a mobile tracking app called Moves that I had heard about through my friend Sachin Monga. He had just published a beautiful set maps showing where he physically spent his time in both Toronto and San Francisco.

His post spurred me to download the app and at the end of my post I promised to share my own set of maps once I had collected enough data points. It’s only been about 3 weeks, but already my maps are starting to fill out, so I thought I would do a release.

The orange lines represent transport of some sort (car, subway, streetcar, and so on) and the green lines represent walking. I don’t cycle very often in the winter (I know, I’m a fair-weather cyclist), so you won’t see any of those lines just yet. However if I posted a map from the summer, I know it would look completely different.

Here’s a first one showing a regional scale:

Here’s a second one showing the city of Toronto:

And here’s a third one showing mostly downtown:

What’s interesting about these maps is how much you can tell about me and the way I move around the city.

For one, there’s a good chance I ski or snowboard given that I’m driving up to Collingwood, Ontario in the winter. You can also see how heavily dependent I am on the Yonge subway line, which is the thickest orange line in the middle of downtown. It’s also interesting to see how localized I am within my neighborhood (St. Lawrence Market). I walk to get groceries. I walk to the gym. I walk to coffee. And the list goes on.

This is fairly typical for people living in urban neighborhoods, but it would be interesting to see where it applies in the city and where it begins to fall apart. I would also imagine that there’s a correlation to the area’s Walk Score, although this (Moves) might actually be a better measure since it’s usage data.

Either way, imagine what cities could do if they had this sort of data for every resident. They would be able to see precise resident flows and then determine exactly where transit and infrastructure investments should be made instead of politicking to determine where they should be made.

That time is coming.

At the beginning of this year I wrote a post about a mobile tracking app called Moves that I had heard about through my friend Sachin Monga. He had just published a beautiful set maps showing where he physically spent his time in both Toronto and San Francisco.

His post spurred me to download the app and at the end of my post I promised to share my own set of maps once I had collected enough data points. It’s only been about 3 weeks, but already my maps are starting to fill out, so I thought I would do a release.

The orange lines represent transport of some sort (car, subway, streetcar, and so on) and the green lines represent walking. I don’t cycle very often in the winter (I know, I’m a fair-weather cyclist), so you won’t see any of those lines just yet. However if I posted a map from the summer, I know it would look completely different.

Here’s a first one showing a regional scale:

Here’s a second one showing the city of Toronto:

And here’s a third one showing mostly downtown:

What’s interesting about these maps is how much you can tell about me and the way I move around the city.

For one, there’s a good chance I ski or snowboard given that I’m driving up to Collingwood, Ontario in the winter. You can also see how heavily dependent I am on the Yonge subway line, which is the thickest orange line in the middle of downtown. It’s also interesting to see how localized I am within my neighborhood (St. Lawrence Market). I walk to get groceries. I walk to the gym. I walk to coffee. And the list goes on.

This is fairly typical for people living in urban neighborhoods, but it would be interesting to see where it applies in the city and where it begins to fall apart. I would also imagine that there’s a correlation to the area’s Walk Score, although this (Moves) might actually be a better measure since it’s usage data.

Either way, imagine what cities could do if they had this sort of data for every resident. They would be able to see precise resident flows and then determine exactly where transit and infrastructure investments should be made instead of politicking to determine where they should be made.

That time is coming.