Human data shows how we move in cities(cities.human.co)
cities.human.co
Human data shows how we move in cities
http://cities.human.co
12 comments
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.
Using a wavelet time frequency analysis is what they generally do to highlight these kinds of patterns when dealing with brain activations of neural populations. It gives you an idea of power of a specific frequency over time [e.g., http://www.lauriefrick.com/wp-content/uploads/2011/07/wavlet...]. And apparently it's already been used for analogous purposes: [
http://www.paramics-online.com/downloads/technicaldocs/wavel...] :-)
Any 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!
No concrete plans yet. We never share any personal identifiable data, without explicit consent of our users. So if we would like to make (parts) of our data publicly available, we have to anonymize and aggregate that data first. For now we're focused on our app first.
Open sourcing data? That seems like a very strange statement.
Strava, a run/bike tracking app, released something similar with their data.
http://labs.strava.com/heatmap/#3/-56.00000/50.00000/blue/bo...
http://labs.strava.com/heatmap/#3/-56.00000/50.00000/blue/bo...
HN discussion:
https://news.ycombinator.com/item?id=7687900
https://news.ycombinator.com/item?id=7687900
This 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.
I'm from Mexico City, and I'm genuinely surprised by the biking activity.
Unfortunately, only in the touristic areas, and near the "Ecobici" routes, there are bike-exclusive lanes. On the other side, drivers feel entitled to use the streets exclusively, and they perceive bikers as a hindrance in their way.
I wanted to commute by bike to my work, but at the end I gave up, because I didn't want to get hit by a car and risk my life like hardcore bikers do.
Unfortunately, only in the touristic areas, and near the "Ecobici" routes, there are bike-exclusive lanes. On the other side, drivers feel entitled to use the streets exclusively, and they perceive bikers as a hindrance in their way.
I wanted to commute by bike to my work, but at the end I gave up, because I didn't want to get hit by a car and risk my life like hardcore bikers do.
Our tracking accuracy overal is good, but slow motorized transport versus bike rides have the highest error rates. That means that in a small percentage of the cases slow, bumpy car rides might get detected as biking and the other way around. Movement patterns vary quite a bit from city to city, especially for public transport. Users can correct detection errors, but that doesn't catch all cases. We have a slight bias towards cycling.
I think the bike data must be skewed. I'm from New York and it shows one of the frequent bike routes to be the helix into the Lincoln Tunnel. You could ride a bike on that helix for about twelve seconds before being crushed by a truck.
At least in Dublin, it seems to confuse Biking with Sailing (see north of Dun Laoghaire pier)
Otherwise very cool!
Otherwise very cool!
Sharp. Thanks!
In some cases we mix up (slow) motorized transport and cycling. We only categorize walking, cycling, running, active (active at one location) and motorized transport, so any other moving activity might end up in one of those categories. For daily use our tracking is pretty accurate for most activity types and users can manually correct any mistakes.
I see also in Dublin, some naughty person had their phone on in an aeroplane :-) You can see the path of the plane landing and taxiing to/from the terminal
The ferries in NYC appear to get classified as walking, but IIRC none of them are drive-on ferries so that's probably fair.
This 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 not familiar with the app, I went straight to that sentence and was baffled about some person who helps people change their place of residence a lot more for 6 weeks, but a lot more... compared to what? Took a while to arrive at "An app named 'Human' helps get people to move around more than they otherwise would within six weeks of beginning usage".
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 not familiar with the app, I went straight to that sentence and was baffled about some person who helps people change their place of residence a lot more for 6 weeks, but a lot more... compared to what? Took a while to arrive at "An app named 'Human' helps get people to move around more than they otherwise would within six weeks of beginning usage".
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...
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...
you can see the different types of transportation across the same city if you see each city's page:
http://cities.human.co/posts/mexico.html
If you liked this, you may also enjoy Foursquare's visualization of checkins, which shows the pulse of the city and the change in human activities (and which areas are populated) as the day progresses:
New York City http://vimeo.com/75413842
San Francisco http://vimeo.com/75416817
Tokyo http://vimeo.com/75404940
New York City http://vimeo.com/75413842
San Francisco http://vimeo.com/75416817
Tokyo http://vimeo.com/75404940
Does anyone know if there is an app that will produce a similar map, but that uses just your own data? I would love to have a map like that that shows where in my city I have been and that would encourage me to see more spots.
OpenPaths (https://openpaths.cc/) is also a good passive location tracking tool. It's not being actively developed anymore and prone to long loading times, but I've been using it for over a year. Their visualization is pretty good and you can export your data in a variety of formats.
Moves (http://moves-app.com) is also good for passive location tracking. Good data export options and some nice mapping integrations with third party services (http://quantifiedself.com/2014/03/map-moves-data/). Disclaimer: Moves is a Facebook entity so caveat emptor
Moves (http://moves-app.com) is also good for passive location tracking. Good data export options and some nice mapping integrations with third party services (http://quantifiedself.com/2014/03/map-moves-data/). Disclaimer: Moves is a Facebook entity so caveat emptor
I haven't used it, but I remember hearing about "Fog of World"[1], which seems like it might be what you're looking for.
[1] https://itunes.apple.com/us/app/fog-of-world/id505367096?mt=...
[1] https://itunes.apple.com/us/app/fog-of-world/id505367096?mt=...
Strava will let you do this if you pay for premium. It's called Personal Heatmaps. It's typically used for running/cycling/swimming, but nothing stops you from using it to track your location.
http://www.strava.com
http://www.strava.com
I use Strava for my runs and rides, and you can get the heatmap (or at least similar) through the third party VeloViewer (http://veloviewer.com/) by looking at your "wheel".
I basically want my always on and exportable Moves (http://moves-app.com/) data to port into "Personal Heatmaps" of Strava.
I basically want my always on and exportable Moves (http://moves-app.com/) data to port into "Personal Heatmaps" of Strava.
Google Location History might have something (even if you don't expect it to) [1]
[1] : https://maps.google.com/locationhistory/b/0/
[1] : https://maps.google.com/locationhistory/b/0/
Mexico 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.
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.
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.
I can't make a meaningful interpretation from this. It looks pretty, but what does it mean?
Does anyone know the name of the music that's playing?
Another interesting metric would be to adjust brightness based on length of journey.