Pedestrian Isochrone Maps

On Monday, October 3rd, the 17th Annual Conference on Walking and Liveable Communities, Walk21 Hongkong has opened its doors to more than 500 participants. One of the speakers will be our Ivo Leiss. In his presentation, he will speak about Walkalytics – EBP’s approach to data analytics for business questions related to pedestrians.

Walking has always been a topic on our agenda. Already in 2013, we have written about accurate analytics for pedestrian accessibility and quality of service for public transport. Since then, we have extended and refined our methodology for pedestrian mobility analysis and successfully applied it to our customers‘ business and location intelligence tasks.

The Walkalytics method

At the heart of our approach are isochrones. Isochrone maps for different modes of locomotion are the hot new thing and there are a lot of interesting blog posts and offerings available, for example on Google Maps Mania or on Medium.

In contrast to the abundant graph-based methods, we take a different path (no pun intended): Our pedestrian isochrones show the precise walking time of a neighborhood for any starting point. Rather than following  a network of streets and paths, they are an aggregate of thousands of individual paths, bundled into one result. As opposed to other isochrone analyses, our approach takes into account desire paths and potential shortcuts across open spaces such as large squares. And it takes less than a second to compute! But a picture is worth a thousand words, and an animated picture is priceless:

A pedestrian isochrone in the city of Bern, calculated with Walkalytics. The caluclation is based on OSM data.
Pedestrian isochrones for a location in the city of Bern, calculated using Walkalytics.

The animation demonstrates our area-based approach: Starting at a particular point, thousands of virtual pedestrians start walking in every possible direction. Every few metres, they ‚measure‘ their walking time and continue walking. Their walking speed depends on the walkability of the ground they are covering: It’s faster to walk on a nice path than on rough terrain; it’s forbidden to walk on a highway or across a railroad and impossible to walk across water. Additionally, we take into account the topography: walking uphill and downhill is associated with different costs depending on the slope. Using the Walkalytics approach, it is also possible to model walking times based on custom rules for the the underlying surfaces and topography.

Your advantages

What are some of the advantages of our approach to computing isochrones for your business or agency?

  • Very detailed results: With one computation, we can show the area that is accessible from any given point within any given timespan, not only for few discrete time steps.
  • We don’t need routing-capable data, we just model every patch of your neighborhood based on its walkability.
  • We can easily combine multiple data sources to model the walkability, like national mapping data, cadastral or surveying data, municipal data, and e.g. OpenStreetMap. Combinating data sources for best coverage is easy. This flexibility of adopting to, and using, different data sources has proven tremendously helpful in recent projects.
  • It’s fast, especially considering the information value of the result: Computing one isochrone at 5 meters resolution with an upper limit of 20 minutes of walking, we analyse literally thousands of individual paths and get hundreds of thousands of walking time measurements as a result. And all this information still can be computed in much less than a second on an ordinary laptop.

Isochrones are certainly interesting! But what is their value for authorities and businesses? What are their use cases? In future blog posts, we will discuss some interesting applications. Meanwhile, you can visit the Walkalytics website, test-run our API or simply play around and create your own animated isochrone by clicking in the map below (computation of these may take up to around 20 seconds, because creating animated GIFs takes much more time than computing the isochrone):

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