Hands on with #MapboxMovement: How to make decisions using movement data

About this episode

Learn how to tell stories and make data-driven decisions using Mapbox Movement, an anonymized dataset of device density, activity, and movement over time drawn from 600M+ users globally contributing 20B+ live location updates daily. Mapbox Movement quantifies changes in movement over time and can be aggregated by state, county, neighborhood, and even block level grid.

After this session, you'll get access to sample data and learn how to process and visualize the data to drive storytelling and decision-making.

The session will answer the following questions:

• What is Mapbox Movement and how is it created?
• What are the popular use cases for Mapbox Movement?
• How do I get sample movement data and sample code?
• How do I use Mapbox tools to transform Movement data and generate insight?
• How do I visualize Movement data using Kepler.gl?

Links

• Email us at movement@mapbox.com to request access to sample #MapboxMovement data.
• Use "What the tile?" to see what a "Z18 tile" looks like.
• Learn more about Mapbox Boundaries.

Q+A

Is it possible to go even further than z18?
No, data is limited to z18 for privacy reasons.

Could you share resources for us to reference the process?
Yes – here is more info and sample data.

If add a new geography to my dataset that has a lot more movement than the ones already in the dataset, all the cell's index values will have to change?
Yes, you'd need to recalculate the baseline because the new geography would be introduced into the distribution.

How does the data are gathered? From what app? Is it any app which uses Mapbox's SDK? Will that app send this anonymized data?
Devices running Mapbox tech with location services turned on. Not just one app. Includes mobile devices, connected vehicles, etc.

‍