A couple of weeks ago, Uber’s Visualization Team released kepler.gl - an Open Source Geospatial Toolbox.
„Build on deck.gl, „kepler.gl is a data-agnostic, high-performance web-based application for visual exploration of large-scale geolocation data sets“ (Uber Engineering Blog)
Uber provides quite impressive maps in their announcement. So I thought to give it a try and check it out.
As we have all seen more than one visualization of taxi trips in New York, I wanted to visualize something else. So why not have a look at bikesharing trips in Hamburg? DB Connect, the bikesharing provider of StadtRad in Hamburg, provides a rich dataset of their bikesharing trips. After a little bit of data preprocessing, I focused on the trips of July 25th, 2016:
The following visualizations describe which routes bikesharing users (probably) have taken. Although DB Connect does not provide GPS data for trips, these routes reflect the shortest path between the start- and end-location of each trip.
Now, let’s have a look at the spatial demand. When and where do trips start?
Popular Routes by Station
Finally, kepler.gl has a nice feature that allows us to focus on the routes that start at each location. In particular, we can analyze where customers are heading to from each station.
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