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The Latest Updates from Uber Visualization

Welcome to the third edition of Uber Visualization Newsletter! Read on for updates on, how to visualize the pulse of a city, and stunning maps from the broader visualization community.

Latest Updates

H3 Layer in has launched its first integration with the H3 open source hexagon library. Users with data associated with H3 hexagons can now display them in with the same options (color, coverage, and height) offered by the hexbin layer.

Text Label in
We added text label control in the point layer to better support text annotation on maps. With this feature, users can assign one data field to the text label and control the style of the text.

H3 Reaches 1,000 Stars
The H3 library now has over 1,000 stars on GitHub and includes newly released, Uber-supported bindings for Java, JavaScript, and Go.

To hear the latest about Kepler and why we open-sourced it from the team behind it, listen to Shan & Abhishek on the latest Geodorable (geospatial) podcast here

Featured Story: What is the pulse of micro-mobility?

As micro-mobility, transportation via compact vehicles such as bikes and scooters, takes off around the world, what can we learn from communities of riders? How can the vitality of movement be visualized? This is precisely what Lime set out to show in their recent 10 million rides announcement through visualizations of their mobility heartbeats in Santa Monica and Paris. Regardless of the market, first and last mile use cases continue to be key drivers of growth, while enabling healthier and more affordable transportation options.

What People Are Building

Using for LiDAR Visualizations
LiDAR provides data as a dense 3D point cloud that can be used to both build and understand rich context in its environment. The team at MapD recently demonstrated how’s Z-axis can be leveraged to visualize multiple layers. 

How 1.3m Data Points Were Mapped
David Blood and Ændrew Rininsland from Financial Times shared five lessons they’ve learned from their UK broadband map project. In their article, they discuss why they chose Mapbox GL JS, React and Uber’s react-map-gl for their tech stack, a combination that enabled them to effectively reduce the upload size and render optimal performance on mobile. 

Maps in the Wild

Contains data supplied by Natural Environment Research Council and © NERC (Centre for Ecology & Hydrology)
Contains National Statistics data © Crown copyright and database right 2011

This map, created by Professor Alasdair Rae from the Department of Urban Studies and Planning at the University of Sheffield, shows daytime population density in the London area for 1km grid cells. On his blog, you can find his step-by-step tutorial that walks through how the map was created and discusses many nuances and tricks for using to create amazing visualizations. In the post, Alasdair also provides a link to the data source (the Natural Environmental Research Council) used for his map, which you can leverage to test out the product and familiarize yourself with

Data Source: German Environmental Agency
These maps, created by Jacob Mendt, CEO and co-founder of PIKOBYTES, visualize the air quality in Germany by looking at days with a maximum O3 concentration over 120 µg/m3 in 2016 (top right), average NO2 concentration 2016 in µg/m3 (bottom right), and average PM10 concentration 2016 in µg/m3 (left). 

Created using, the visualization above depicts trips taken via a variety of modes and transit agencies throughout San Francisco as simulated in BEAM. Check out the full animation, here.

Share yours with us! Tweet @ubereng with #keplergl!

Want to share feedback, discuss possible collaborations, or ask a question about Contact us at!

Things to Read

Visual journalism then and now: How much harder was it to make high-quality maps without computers? Graham Douglas takes us on a journey back in time to 1987 when he started building maps for The Economist.
Representing uncertainty: We’re certain that this list, compiled by Professor Enrico Bertini from New York University, has the best resources (including talks, articles, and papers) on visualizing uncertainty. 
Possible trajectories of Florence: One of the most compelling uses of uncertainty this month was this tracker of Hurricane Florence, created by Chris Canipe and Lazaro Gamio for Axios. The visualization depicts all possible paths Florence could have taken.
No exception to climate change: Antti Lipponen from the Finnish Meteorological Institute released a video that shows temperature anomalies by country over more than a century, indicating that with no exceptions all countries have gotten significantly hotter.
Your hometown is also getting hotter: The New York Times published this visualization that shows how much hotter the place you’re from has gotten since you were born and how much temperatures there will increase over the next decades.

External Engagement

We presented on at FEDAY 2018, a forum for discussion around cutting edge front-end technologies, in Guangzhou, China this year, as well as at Media Party 2018 in Buenos Aires, a conference for journalists and media enthusiasts from all over Latin America. During these events, we talked about building advanced geospatial visualizations with the suite of frameworks and held a hands-on workshop to show journalists how they can use the tool in their day-to-day work.
Creator of, Shan He speaks at FEDAY 2018. Photo credit:

We were invited to demo our open source visualization frameworks at the @SCALE conference.
Our booth at the @SCALE conference

Last but not least, Uber is hosting our first-ever Uber Open Summit on November 15, 2018. This is a one-day summit for developers and community leaders advancing open source collaboration and innovation at scale. Featured projects include Pyro, Petastorm, Horovod, Fusion.js, Cadence, Jaeger, M3, our Big Data stack, and our data visualization suite, including We will also host a workshop that spotlights our data visualization and H3 work. Interested in joining us? RSVP here!

Thanks for reading! 

- The Uber Visualization Team

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