A new map in town: MapKit JS by Apple

Back in 2011, #TeamEBP has written about the usage of geo.admin.ch and compared it to other map services like Google. A year later, Apple joined the party of map providers and introduced Apple Maps to the world, with one caveat: It was only available on Apple devices. With Apple’s developer conference last week, this has changed: Apple introduced a new Javascript library called MapKit JS from Apple – this means that you can now embed a webmap by Apple on any of your websites. Currently the API is in beta, but the documentation is already available, including sample code. If you need even more information: check the WWDC session video, the demos begin at 26:00, 43:45, the slides are at available as PDF.

Unfortunately the basemap quality is not that good for Switzerland (compared to California, at least), so this blog post is not suggesting you to migrate and use it in production. However, you can get inspired, the codebase is a sum of rich and beautiful APIs with many concepts borrowed from the MapKit native which exists in iOS since its first release, more than 10 years ago.

One important thing to note is pricing: As we’ve written in 2011, no webmap comes for free, if used heavily. Apple’s expected pricing strategy according to the presentation is interesting: you can use 250’000 map initializations and up to 25’000 service requests (geocoding, search with autocomplete, directions) for free, per day (sic!). This is about 10 times more than what Google charges you with their recent price change (One caveat: it’s hard to compare pricing for mapping APIs directly, so take this number with a grain of salt). Note however, that you need an API key in order to use MapKit JS, for which an Apple Developer account is necessary (which again costs you CHF 109 per year).

I’ve also made a simple CodePen Demo with a WMTS layer from ArcGIS Online and walking directions from Apple’s routing service. The WMTS layer shows a quality of service map for public transportation stops, computed with Walkalytics.

See the Pen EBP MapKitJS Demo by Stephan Heuel (@ping13) on CodePen.

Here is a direct link to the JS code of the demo.

Are you interested in using MapKit JS standalone or in combination with other mapping services? Get in touch with Stephan Heuel or myself, we would love to talk with you. 

Pedestrian Reachability Analysis for Hyperlocal Marketing

Since 2013, EBP has been developing and refining Walkalytics, an approach to data analytics for business-relevant questions regarding pedestrian mobility. At the heart of the approach lie isochrones, which are calculated for every square meter of an area-of-interest. In the early stages, we successfully applied Walkalytics mainly in urban and transportation planning. In this blog post, however, I want to demonstrate how Walkalytics can help you in geomarketing on very small scales.

Example 1: Narrow the audience of a direct mailing campaign

As a first example, let’s assume you are big transportation agency with a large customer database that also features a postal address for each of your customers. Let’s further assume you want to send some customers a special offer by mail – but only to the segment of customers who are most likely to accept your offer. In other words, you want to narrow your target audience, if only to save printing and postage costs. A sensible criterion to optimize your campaign’s target audience could be the time that customers take to reach the next transit stop (or any other customer contact point of your liking) on foot.

With Walkalytics, we have the solution to your task: We’ve taken all Swiss addresses from the federal register of buildings and calculated the walking time from each address point to the closest transit stop. You can use this massive dataset to narrow the segment of customers that will be targeted in your campaign. You don’t even have to ask your in-house geodata expert to help you with your filtering: everything is done directly in your customer database based on our augmentation of your CRM data!

General Post Office mail sorting room, Wellington (source Archive New Zealand)

Example 2: Find the optimal location for your customer contact points

Let’s assume you are a manager in a retail company which wants to find the optimal locations of new service points. As you have a business with lots of walk-in customers (i.e. pedestrians), this means you want to find locations that serve many non- or under-served people within a sensible walking distance or time – say within 5 minutes walking time.

For addressing this need, we took advantage of another government data set: The population and household statistics (STATPOP) and the business demography statistics (STATENT) have a number of indicators that are measured in 100×100 meter units all over Switzerland. For each of the effectively 360,000 units, we calculated a walking isochrone and aggregated relevant indicators such as the reachable residential population or reachable number of, e.g., third sector employees. After completion of our analysis, we know for each 100×100 meter square in Switzerland how many people can reach this location within 5, 10 or 15 minutes of walking. Since your business relies on walk-in customers, this informs your choice of where to open your next service point(s).

Workforce reachable within 5 minutes of walking, in Geneva. Red=high number of people reached, blue=low number.
Residential population reachable within 5 minutes of walking, in Geneva (red=high, blue=low).

Did these examples whet your appetite for geo-augmenting your customer and site data? Are you, for example, interested in filtering your customer database according to the reachibility of your service points? Do you want to optimize locations based on socio-economic statistics? Let’s have a talk, e.g. during GEOSummit in Bern or online using e-mail or Twitter!

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):

Forget Apps – Bots Are the Future of Geo

Update 2016-12-01: We have a second version of our bot and a landing page at http://www.traindelaybot.ch. It now supports Facebook Messenger, Skype und Slack.

The title of this blog post may seem hyperbolic, but during the last few months there has been an increasing
buzz on personal assistants and bots
like Amazon’s Echo, Apple’s Siri or Facebook’s „M“ – the latter being a shopping assistant in Facebook’s Messenger app. Some people proclaim that we experience a new generation of user interfaces: The conversational UX where users interact with a system by „simply saying“ what they want. Last week, [Microsoft introduced developer frameworks for conversational bots](Microsoft introduced conversational frameworks) as a core part of their cloud strategy. And just yesterday, Facebook announced their Bot API for their Messenger.

When new concepts and trends in technology occur, it is a good idea to get first-hand practical experience before adding to that first rising slope in the hype cycle. So, during the last months I made some experiments that I now want to share with you.

Not yet an uprising, but the bots are slowly coming… photo: Francesco Mondada, Michael Bonani, CC-SA3.0, Source

„Forget Apps – Bots Are the Future of Geo“ weiterlesen

Wie gut ist ein Standort mit Bahn und Bus erschlossen?

Update August 2014: Die im Folgenden beschriebene flächenhafte Berechnungsmethode können Sie jetzt auch in ihren Projekten einsetzen: Unter walkalytics.com finden Sie unser weiterreichendes Angebot für fussgängergerechte Distanzen und darauf aufbauende Analyse. Auch weiterhin beantworten Stephan Heuel und ich gerne Ihre Fragen.

Vom Zirkel …

Die Erschliessung mit dem öffentlichen Verkehr ist in der Raumplanung und insbesondere bei der Wahl eines Standorts von grosser Bedeutung. Das Bundesamt für Raumentwicklung (ARE) hat im Jahr 2010 einen Grundlagenbericht veröffentlicht, der das Thema Erschliessung und Erreichbarkeit in der Schweiz untersucht. Ein wichtiges Instrument zur Operationalisierung der Erschliessung sind die sogenannten ÖV-Güteklassen: Zur Ermittlung dieser Güteklassen werden Haltestellen gemäss ihrer Fahrplanfrequenz kategorisiert und die Güteklasse in bestimmten Einzugsbereichen um die Haltestelle entsprechend festgelegt. Die Güteklassen beruhen auf der VSS Norm 640 290 und werden je nach Kanton oder Bund zum Teil unterschiedlich umgesetzt (eine neuere Norm (SN 640 281) existiert, wird aber noch kaum implementiert). Das ARE hat ihre Berechnungsmethode in einem PDF dokumentiert, der Kanton Zürich hat kürzlich seine Ergebnisse mit erweiterter Methodik im neuen GIS-Browser veröffentlicht:

ÖV-Güteklassen im Kanton Zürich

ÖV-Güteklassen im Kanton Zürich


Wenn man die Ergebnisse des Kantons Zürich und des ARE betrachtet, stellt man fest, dass die Erschliessung um die Haltestellen in konzentrischen Kreisflächen abgebildet wird. Diese Flächen bilden aber bei weitem nicht die wirkliche Fussgängermobilität ab: Fehlende Fusswege, Flüsse und Autobahnen entgehen diesen Analysen, sind aber für die tatsächliche Erschliessung „per pedes“ essentiell.

… zur tatsächlich zurückgelegten Distanz

Es geht aber auch genauer: Wir haben einen rasterbasierten Ansatz entwickelt, der es uns erlaubt, Fussgängermobilität flächendeckend zu modellieren. Für ein Beispiel wurde uns vom ARE ein Datensatz mit den Erschliessungskategorien (1-5) von ÖV-Haltestellen zur Verfügung gestellt (danke!). Wir haben uns bei der Berechnung auf fünfzig Haltestellen im Raum Bern-Ittigen beschränkt. Für die Ermittlung der ÖV-Güteklassen mit Distanzen gemäss ARE haben wir die Distanzen nicht – wie es die Methodik des ARE vorsieht – „mit dem Zirkel“ abgetragen, sondern als Fussgängerdistanzen mit unserem Ansatz modelliert. Den Vergleich der beiden Methoden sehen Sie in der folgenden Abbildung:

(Klicken zum Vergrössern) Vergleich zwischen ÖV-Güteklassen gemäss modellierter Fussgängerdistanz (links; Ansatz EBP) und gemäss Standard des Bundesamts für Raumentwicklung (ARE) (rechts). Die 50 in unserer Berechnung berücksichtigten Haltestellen sind mit ihrer Haltestellenkategorie (1: am besten erschlossen, 5: am schlechtesten erschlossen) eingezeichnet.
(Klicken zum Vergrössern) Vergleich zwischen ÖV-Güteklassen gemäss modellierter Fussgängerdistanz (links; Ansatz EBP) und gemäss Methode des Bundesamts für Raumentwicklung (ARE) (rechts). Die 50 in unserer Berechnung berücksichtigten Haltestellen sind mit ihrer Haltestellenkategorie (1: am besten erschlossen, 5: am schlechtesten erschlossen) eingezeichnet.


„Wie gut ist ein Standort mit Bahn und Bus erschlossen?“ weiterlesen