I just came across an interesting web app created by geographer and programmer Andrew Hardin that maps public transit travel times for San Francisco, Seattle, Boulder and Denver.

The app allows you to click on a location within one of these cities (or enter an address) and then receive a visual representation of travel times from that location.

Both public transit and walking are factored in, and the fastest of the two is then modeled. The public transit data is taken from each respective authority and is similar to the data used by Google Maps.

With these sorts of applications, I always wonder what it might look like overlaid with additional data points, such as home prices. Intuitively I would expect the best connected neighborhoods to also have some of the highest real estate values.

I just came across an interesting web app created by geographer and programmer Andrew Hardin that maps public transit travel times for San Francisco, Seattle, Boulder and Denver.

The app allows you to click on a location within one of these cities (or enter an address) and then receive a visual representation of travel times from that location.

Both public transit and walking are factored in, and the fastest of the two is then modeled. The public transit data is taken from each respective authority and is similar to the data used by Google Maps.

With these sorts of applications, I always wonder what it might look like overlaid with additional data points, such as home prices. Intuitively I would expect the best connected neighborhoods to also have some of the highest real estate values.