At least in Dublin, it seems to confuse Biking with Sailing (see north of Dun Laoghaire pier) Otherwise very cool!
The ferries in NYC appear to get classified as walking, but IIRC none of them are drive-on ferries so that's probably fair.
Human data shows how we move in cities
11–20 of 36 posts
Re: Human data shows how we move in cities
#12This reminded me of a fragment from Cryptonomicon about collecting history of elevation of people walking around the city and trying to reconstruct a street map from it. While an interesting exercise, we just carry precise position beacons with us these days.
Re: Human data shows how we move in cities
#13This is pretty cool, although it would be nice to see the different types of transportation across the same city. I see dramatic differences in the visualizations, sure, but they seem as dramatic as the differences in the layout and structure of these cities. While I'm giving feedback, I must say I had to pause and re-read this sentence many times: "Human helps people move almost twice as much in six weeks". As I'm n…
Thanks for the feedback. We rendered visuals for different activities in all cities. Click one of the cities on the homepage for details. We've also shared all visuals (dark and light) and some bonus gifs on Dropbox: https://www.dropbox.com/sh/58chppkj2ckim7s/AAAchKhSL56mjaaiA...
New York is missing a graphic
Re: Human data shows how we move in cities
#14Strava, a run/bike tracking app, released something similar with their data. http://labs.strava.com/heatmap/#3/-56.00000/50.00000/blue/bo...
HN discussion:
Re: Human data shows how we move in cities
#15Perhaps the decay times on the trails is too long, but I can't really detect any patterns here, other than that people seem to walk, run, cycle and drive down roads. After a few mins, all this seems to do is highlight the road structure of a city. A shorter trail decay would highlight the people commuting and show activity for transport type by time of day. Another interesting metric would be to adjust brightness bas…
Good point. I played around with different decay times a lot, but it was very hard to settle on a decay time and opacity settings that worked for most cities, since the data set from city to city was varying in size. If I would re-render the movies, I'd definitely do try renders with lower decay times, especially for cities like NY, LA, etc.
It might be interesting to see whether or not an ideal decay time correlates with anything.
Re: Human data shows how we move in cities
#16Earlier quoted context omitted.
Thanks for the feedback. We rendered visuals for different activities in all cities. Click one of the cities on the homepage for details. We've also shared all visuals (dark and light) and some bonus gifs on Dropbox: https://www.dropbox.com/sh/58chppkj2ckim7s/AAAchKhSL56mjaaiA...
New York is missing a graphic
Thanks! Fixed.
Re: Human data shows how we move in cities
#17Mexico City is not showing up as a leader in walking. I find that hard to believe.
Re: Human data shows how we move in cities
#18Mexico City is not showing up as a leader in walking. I find that hard to believe.
The data is coming from the subset of people who have iPhones. So you can have 30 million people walking, but if only a few are rich enough to have an iPhone, then they are invisible.
Re: Human data shows how we move in cities
#19Any chance at open sourcing the data? There are other cities that would be interesting to see that are not included in your sample. Are you interested in licensing out use of the data to 3rd parties? So much data!
Re: Human data shows how we move in cities
#20Mexico City is not showing up as a leader in walking. I find that hard to believe.
This is a really self-selected data set. If you look at the New York map you'd think people didn't exist in most of Brooklyn and Queens.
Ditto Vancouver where I originally come from - lots of activity downtown and in rich, young neighborhoods, but nearly zero activity in middle class or older neighborhoods.
It's not just selecting for iPhone users, it's selecting for wealthy, young, iPhone users. On a more meta level these maps are an interesting proxy for wealth, race, and age.