Sightlines Map

Views of and from the Statue of Liberty are iconic. They can be a part of our mental repertoire of images of New York City even for those who have not experienced it firsthand. Recognizing this view is very different from knowing the city that it represents. However, using its familiar perspective as a lens to view public datasets can be a powerful way to humanize data about the city.

The sightlines maps use the Statue of Liberty(and other landmarks) as its starting point for experimentation, and asks:

Where in the city can you see the statue?

What and who does the statue see in the city?

And what is the significance of this visibility?

Sightlines are reciprocal in the abstract – the same map can be drawn of the view from the statue of liberty as of the places that can see the statue. In New York City, we are fortunate to have footprints of buildings and elevation data updated yearly, as well as a detailed tree census with canopy size and height of street trees. Using these three physical public datasets, we can apply simple math iteratively to calculate exactly which buildings have a direct sightline to and from the Statue of Liberty, creating a viewshed map in the same spirit as a watershed.

We can then overlay visible locations with property, business, and demographic data to map who and what this view contains. Using this method, the New York skyline can be contextualized not only by the characteristics of its architecture but also by the people living and working within this view. When viewing this series of public data maps, audiences can find not only where they can see the statue of liberty in the city, but also find who they are looking at when they gaze out from the statue itself.

The original prototype below was presented at the North American Cartographic Information Society Annual Conference in October 2017.


Download the full poster.

A new interactive version of this map is in progress and can be found at here.

Screen Shot 2018-01-26 at 2.25.58 PMScreen Shot 2018-01-26 at 2.26.09 PMScreen Shot 2018-01-26 at 2.26.25 PM