Determine the Transit Score for your Home/Business using Azure Maps

Moovit, the world’s largest urban mobility data and analytics company, integrates its public transit information with Azure Maps to help developers build richer apps using public transit data. To learn more about the public transit data , you can explore the Mobility API's in the Azure Maps documentation. 

Businesses, Realtors & Retailers can determine the profitability of a business (or the appeal of a home) based on its Walk Score and Transit Score.  The Transit Score is a two digit numbers that enable businesses to determine how well a location is served by public transit on a scale from 0 to 100.

 

My previous post on analyzing the catchment area for retail provides a good basis for calculating the walk score for a location. You can use the Python code sample that I made available on GitHub, as the basis for building your own walk score for different business drivers and disruptors (I would love to see the results).

 

In this post, I experiment with the Mobility API in Azure Maps to determine how accessible a location is to Public Transit. I built the code using Jupyter Notebooks (Azure Notebooks) and Python. I have built out the process for getting details of the nearby transit options for any address as well as the details of every line that goes through those stops. Using this, you can score, the number of stops, the distance to the stops, the routes served by the stops and the destinations to arrive at a Transit Score for your location. 

 

The returned data can be used for calculating the Transit Score based on:

• Number of Transit Stops within the specified Radius
• Distance to the Transit Stops from your location
• Number of lines that go through the Transit Stops
• Destinations of each of the lines
• Frequency & timings of the transit options
• & more

I ran the analysis for an address in Seattle : 400, Pine Street, Seattle (you can edit this address in the code and run your own analysis). The results showed me the transit stops around the location. I also called additional API's to get details of all the lines that pass through the stops and their destinations. I also use the Get Route Directions API to calculate the distance and time to walk to each of the stops. All of this information can be used to build your own transit scoring mechanism for locations. 

Here is a sample of the results that I extracted:

 

 

You can download the code sample from GitHub

1. Get your Free Azure Account
2. Follow these steps for creating a free Azure Maps Subscription Key
3. Upload the code to Azure Notebooks to test, personalize and extend it.