13 thoughts on “Map of the Day: Where People Run, Walk, and Bike in Minneapolis/St. Paul”
jhop
Poor and disadvantaged areas stick out like a sore thumb. I do see some of the areas with an older population, such as Shoreview have lower overall highlighting. Very interesting data.
The data comes from RunKeeper. It is an iphone app that lets the user track their exercise. I would guess there is a systematic bias against older and poorer people in this data because both of those demographics are less likely to have an iphone and use an app like this. This systematic bias likely explains some of the drop in trips in areas with predominantly poor and old people.
Joseph Totten
This would also be biased towards recreation, wouldn’t it? I personally do not use apps for my daily commutes or errands (typically).
Biased towards recreation/physical training, yes. But research into the Strava app uses in San Francisco suggests that just under half of the bicycle data points were for commutes. During those time periods when I bike-commuted in Norfolk, I used it for them as well as for errand runs.
Jason Goray
It also works on Android. FWIW, I’m only a sample size of one, but I use it for my daily commute for a few reasons:
* It helps me see which routes and conditions take how long so I can better predict when I’ll get places
* Since I have it linked to gympact and the commute is an easy way to make my weekly pact.
* I work someplace with a relatively flexible schedule and it makes it easy for me to check when I got in and verify that I’ve been working enough hours.
Similar maps have been made in the past from Strava (an app similar to RunKeeper) data. Here’s their map server, for an area similar to what David displayed:
I looked into these datasets a bit for work and focused on Strava’s. You can purchase a license to a region for whatever use you’d like, for a significant fee. Besides the high cost, the potential biases discussed by other commentators made us recognize that while these are fun images, their usefulness for planning purposes can be limited. But like any dataset, it’s a lot better than nothing. And they’re kinda pretty too!
Ron
Very useful for Bike Planners. Shows where people actually ride. Like tracks in the snow for Ped Planners.
Thomas Mercier
Interestingly there are also bike tracks in the Strava dataset that exist on groomed XC ski trails located on what is a golf course in summer. My guess is some folks use the aps for XC skiing and just don’t change the settings.
In some cases the data is useful, but it isn’t always as clear as one would like.
Nate Pentz
Shockingly, Most of the areas in North Mpls that are lighted are where there are bike paths/lanes.
Poor and disadvantaged areas stick out like a sore thumb. I do see some of the areas with an older population, such as Shoreview have lower overall highlighting. Very interesting data.
yeah… where’d the data come from?
The data comes from RunKeeper. It is an iphone app that lets the user track their exercise. I would guess there is a systematic bias against older and poorer people in this data because both of those demographics are less likely to have an iphone and use an app like this. This systematic bias likely explains some of the drop in trips in areas with predominantly poor and old people.
This would also be biased towards recreation, wouldn’t it? I personally do not use apps for my daily commutes or errands (typically).
Biased towards recreation/physical training, yes. But research into the Strava app uses in San Francisco suggests that just under half of the bicycle data points were for commutes. During those time periods when I bike-commuted in Norfolk, I used it for them as well as for errand runs.
It also works on Android. FWIW, I’m only a sample size of one, but I use it for my daily commute for a few reasons:
* It helps me see which routes and conditions take how long so I can better predict when I’ll get places
* Since I have it linked to gympact and the commute is an easy way to make my weekly pact.
* I work someplace with a relatively flexible schedule and it makes it easy for me to check when I got in and verify that I’ve been working enough hours.
Similar maps have been made in the past from Strava (an app similar to RunKeeper) data. Here’s their map server, for an area similar to what David displayed:
http://labs.strava.com/heatmap/#12/-93.26715/44.94892/blue/both
I looked into these datasets a bit for work and focused on Strava’s. You can purchase a license to a region for whatever use you’d like, for a significant fee. Besides the high cost, the potential biases discussed by other commentators made us recognize that while these are fun images, their usefulness for planning purposes can be limited. But like any dataset, it’s a lot better than nothing. And they’re kinda pretty too!
Very useful for Bike Planners. Shows where people actually ride. Like tracks in the snow for Ped Planners.
Interestingly there are also bike tracks in the Strava dataset that exist on groomed XC ski trails located on what is a golf course in summer. My guess is some folks use the aps for XC skiing and just don’t change the settings.
In some cases the data is useful, but it isn’t always as clear as one would like.
Shockingly, Most of the areas in North Mpls that are lighted are where there are bike paths/lanes.
sooo, what is the color gradient representing?
Frequency. In short, the brighter the color, the higher the frequency.