Taxi! is an analytical model that maps the trip data for 10,000 taxi rides over the course of 24 hours. Geographic location data for the origin and destination of each ride is combined with waypoint data collected from the Google Maps API in order to generate a geographically accurate representation of the trip. We used data from taxi rides originating or ending in the neighborhoods of Lincoln center or Bryant Park. The visualization recreates a ‘breathing’ map of Manhattan based on the migration of vehicles across the city over a period of 24 hours, displaying periods of intensity, density and decreased activity.
This project was a collaboration between Tom McKeogh, Eliza Montgomery and Juan F Saldarriaga. It was done for SEARCH class taught by Mark Collins and Toru Hasegawa (Proxy), at GSAPP, Columbia University, Fall 2011.
We acknowledge the support of the CUNY High Performance Computing Center under NSF Grants No. CNS-0855217 and No. CNS-0958379.
For any additional information please contact Juan Francisco Saldarriaga at firstname.lastname@example.org
See more data visualizations at http://juanfrans.com
Music by Rob Viola http://statikluft.com/
72 hours of geotagged tweets were logged using the twitter streaming API. Using processing, the tweet events are shown at the correct relative time and place using a blue dot. If the same user tweeted 2 or more times during the 72 hour period, their tweets will be connected in time and place with a yellow dot. Slow-moving and stationary yellow dots have been removed from the Animation to accentuate regional movement patterns.
Rush hour migrations into and out of the center city can be seen, as well as several other cross-borough movement patterns.