Programming Fundamentals » bert_anti_map_viz

Final version of GPS visualization project for the data workshop

balcaen.bert@iaac.net — Tue, 20 Nov 2012 12:10:33 +0000

Video of the final version:

A walk in Barcelona. Visualization of GPS data. from Bert Balcaen on Vimeo.

Here are some notes on how I got there.

I experimented with adding the street names next to the trail. This puts more emphasis on the sequence of the streets. However, the label positioning (overlaps) seemed like a problem I couldn’t solve quickly. I found a nice solution from Moritz Stefaner that uses forces to make sure labels don’t overlap each other. Looks like a very good starting point for a future project.

In this video I used another data set. The one in the previous videos is me running. Here I’m using a recording of an evening walk through the city. There are some interesting moments: me trying to find a shop (without using GPS) and getting a little bit lost, the rythm of my walk, stopping for traffic lights, etc. Also watch how the GPS gets confused and the data starts to get noisy when I spend some time in a supermarket. I decided not to clean up the data and just leave it like it was.

I also changed the panning. Instead of keeping the current location always in the center of the screen, I added some very simple tweening so the map doesn’t center immediately on the last position. I think it conveys the feeling of space a little bit better like that.

Then I took another look at how the data was being displayed. I thought it would be good to give the viewer some more information about what kind of walk this was, so I added time and distance. I also included a legend for the colors because I always had to explain what they meant when I was showing the video to someone.

I’m pretty satisfied about this project, giving the time constraints we had (just a few days). Here are some suggestions I got from people who saw it:

Use the compass to show what I was looking at during the walk, and show those places using a POI database.
Try out other ways of visualizing the trail.

Progress on GPS visualization project for the data workshop, part 2

balcaen.bert@iaac.net — Sun, 18 Nov 2012 10:00:27 +0000

Visualization of GPS data, iteration 3 from Bert Balcaen on Vimeo.

In this video the color of the trail corresponds to its location on Google Maps. I spend a lot of time on this, but I think it’s adding a very interesting layer to the visualization. I’m using the Static Maps API from Google to download map images with a PHP script and then check the color of the pixel in the center. I turned off all text labels in the maps. Here’s an example:

I also decided that a little more context would be good, so I added the street names using reverse geocoding with OpenStreetMap. Example:

http://nominatim.openstreetmap.org/reverse?format=xml&lat=52.5487429714954&lon=-1.81602098644987&zoom=18&addressdetails=1&format=json

The data from the AntiMap app is very detailed. I got banned a couple of times because I was exceeding the rate limit of these API’s. Most of them allow only a certain amount of queries per hour. It also means the process of getting the street names and colors can take ages. For now I’m only doing this for a fraction of the data.

I’m experimenting with typography. Here I set the type in Futura Extra Bold Condensed. It’s a typeface from the same area where some of my inspiration comes from (the 1930s & the emergence of the flaneur).

I created the video’s by using saveFrame(“screenshot-######.png”) and ffmpeg:

ffmpeg -i screenshot-00%4d.png -vcodec libx264 test.avi

Progress on GPS visualization project for the data workshop

balcaen.bert@iaac.net — Sat, 17 Nov 2012 16:14:40 +0000

See: data workshop

I wanted to get a feeling for the data so I started off by creating a quick and dirty Processing sketch that visualizes the location data recorded with AntiMap. I used Unfolding Maps, a very complete and well-made library for using maps inside Processing. Here is a screenshot.

That felt very static, and the core of my concept is how walking brings the city to life. I wanted to see how it would look like if I animated the trail, showing only a part of it. I also cleaned up the code a bit so it would be a bit easier to work with. This is the result:

Visualization of GPS data, iteration 1 from Bert Balcaen on Vimeo.

It draws a circle for each location. The circles grow and gradually become more transparent. It’s simple but interesting: it brings the data to life.

Cristobal suggested to use the map colors for the trail. I really like that idea, so I thought that would be a good next step. Here’s a video:

Visualization of GPS data, iteration 2 from Bert Balcaen on Vimeo.

However, at the moment I’m stuck on how to pick the right colors. The Unfolding library uses the GLGraphics for drawing maps, making the whole thing fast by using OpenGL. It also makes some basic things more complicated. For example: it seems that the get() function to find a color’s pixel doesn’t work as it should. I think some sort of offset is applied.

Project plan GPS visualization project for the data workshop

balcaen.bert@iaac.net — Wed, 14 Nov 2012 16:21:00 +0000

Core of the idea

Walking brings the city alive. The piece will visualize data from walks and runs.
We all create our own version of the city. The visualization will not include a typical map – it will show how we create Barcelona with our walks. People watching the piece might be able to recognize neighbourhoods from the patterns generated by the walks.
I will focus on how walking is an act that exists only in the moment. The route will not be shown in its entirety.
The visualization of the location trail will use the standard map colors. This can help people to guess where to walker is, and will also reveal something about the qualities of the space used during the walk: main roads, sidewalks, buildings, parcs, …
Each GPS record is visualized as a line. Length is inversely related to speed. Short lines = fast. Long = slow. Direction of the line correspond to the compass.
Add basic info display with speed etc.

Phase 2: multiple routes

Check with running file, see if it’s different enough.

Phase 3: POI data

POI data is displayed along the route. The amount of POI’s displayed depends on the speed in a segment of a route. Slow sections have more POI’s.
POI’s popup with name when passing by, and disappear when moving further.
Data sources for POI’s: Foursquare.
Add street names to info display.

Data workshop – ideas, research, feedback

balcaen.bert@iaac.net — Wed, 14 Nov 2012 13:18:52 +0000

Assignment

Visualize GPS & compass data recorded with AntiMap.

Notes on using Antimap

I experimented a bit with the iPhone version of the app. It works well. Here are a few things that are good to know:

The app should stay in the foreground. Don’t put your phone in stand by, don’t minimize the app, and don’t switch to another app. If you do this the recording will be stopped and there is no way to continue it. The CSV file is saved though, to in the theory you can start another session and somehow glue to the CSV’s together.
Using GPS requires a lot of energy. Best to have a full charge if you want to record a long session.
Rotation: I put it in the pocket of my shirt. It works well, but here is the trick: if you put in your pocket with the screen facing towards you, then the angle will be correct. If the screen is facing away from you you need to do 360 – the angle from the CSV to get the correct angle.

I made a quick and dirty sketch that visualizes the data on a map.

Idea: walking as a form of drawing that reveals the city

Inspiration: Michel de Certeau

De Certeau is a French philosopher and sociologist from the 1960s. For him, walking in the city is a creative act. It is not the city planners that make the city, it’s the people in it that bring it to life he says. Here is a a good summary on de Certeau.

Previous project: 35 days in NYC

In a previous project I visualized 35 days of location data recorded with OpenPaths. I like it because it maps my experience of the city – which is different from someone else’s and the official city map. It shows my New York. I also like it visually: it’s organic, instead of the typical straight lines between points.

This assignment could be a nice way to revisit that project and to elaborate it. Maybe an animation can be interesting. Or maybe I should only show an animated part of the trail, instead of the everything at the same time. Also: the data I used was not continuous, because OpenPaths works in a strange way and only takes a snapshot every once in a while.

References

YesYesNo did a similar project for Nike+. Here the link between data and visualization very abstract. Maybe it’s nice to have it tighter?

Techniques

I will use a particle system that emits particles at the current location (lat/long). Speed could influence how it reacts with other particles. Fast: repel other particles. Slow: attract. Compass: direction. I recorded a couple of different styles of walks: one very functional (from home to IAAC), one while running, another one going home with some detours, … Could be nice to have them all together according to same algorithm, and hopefully see some interesting differences.

Feedback from Cristobal

Use colors from a real map, giving people hints about the areas where GPS data was recorded. “You could use a colour palette that will be white (for streets), gray (for buildings) and green (for parks). I think it could be really easy to identify the visuals as an abstract representation of a map because we associate those colours to Google maps.” Great idea. I already have a basic Processing sketch that loads the GPS data and displays it on map. Shouldn’t be that hard to have it pick up the colors from the map and use these for the particles.
“In this case, it would be awesome if the app grabs the POI along your path, affecting the visuals in a special manner. It also make sense what you mentioned about the speed at which you travel as a way to set how much you can enjoy the trip (going slow = getting more details of the city) versus a fast transportation.” I thought about this before, but it seemed to conflict a bit with the idea of “people create the city” and when I think about POI data, McDonalds and Starbucks are the first things that come to mind. But maybe I should just explore Foursquare & co a bit better, and see if there is a good way to filter out companies and administrative location and see what kind of data this gives. For example, the guys from the startup I used to work with had tagged the bench in the park next to our office.