A typical city bike map shows painted bike lanes, separated facilities, and sharrows. But what is it actually like to ride a bike on these facilities?
New York City 2019 Bike Map (section)
Yes, maps have their limits. But I think there's room for growth in using them to represent cycling conditions. How can we move past the existing way of mapping bike facilities to reflect the conditions everyday people experience on the street? This piece seeks to explore mapping cycling experience and serve as a discussion point.
The power of maps
The city bike map both makes cycling simpler and more complicated. It builds a language around what people should expect if they are to cycle on a street, but this language is not well-connected to the wider public. Using terms like "sharrows" and "buffered bike lanes" professionalizes it and serves as a veil to the conditions on the street.
City bike maps can also play a role in public accountability. As governments work toward their bike plans, they add facilities and increase coverage on the map. Laudable, but what do you get when you have extensive facilities that don't focus on the experience people have? A full map, but also stressful conditions on the street and a mode of transportation that is not practical or accessible to all.
The city bike map thus has potential to be more transparent into the actual conditions on the street. Can we create a map where people (a) don't have to learn a new professional vocabulary and (b) can holistically understand conditions on the street?
Towards a bicycling environment
What if instead of mapping bike facilities (which are a means to an end), we gave a fuller picture of what it's like to ride there, or the "bicycling environment"? Here's my take on approaching this (using New York City as an example):
1. Build criteria of pleasant cycling environments, develop a shared understanding
The first here question is: how can a bicycling environment be measured? There are lots of variables that affect the experience someone has riding, so these choices will not be perfect and reflect everyone's opinion. What it is an opportunity for though, is to start a discussion on what a positive cycling environment is- to locally develop a shared understanding.
2. Gathering data
The qualitative descriptions of what constitutes a pleasant cycling environment will then need to be translated into concrete criteria. The following are a reference point that I came up with (yours might look different):
Datasets used as criteria for the bicycling environment in NYC (for "allocation of space": Landsat satellite imagery)
The final criteria you choose will be dependent on the datasets you have available. You can also get creative here and add in less traditional data that is important for the experience people have cycling. For example: noise levels (especially relevant in New York City) or how "people-friendly" a place is.
My take on measuring a "people-friendly" street (taken from other project here)
If you don't have hard data that can be weighted, perhaps add a qualitative element to the map that can be experienced, such as the sound you hear while riding down a street (example project here).
3. Weighing criteria, calculations
To get end values of how pleasant it is to ride a bike on each street, you will need to weigh your criteria to get to a final value. Especially if your criteria are complex or if you are working with a large area, you will want to use GIS. This process will probably involve re-projections, clips, and reclassifications, among other GIS tools. The city bike route classifications, for example, will need to be reclassified according to values you choose for each type of infrastructure (see example below).
Sample reclass values for select NYC bike route classifications (0=low, 9=high)
4. Making a map
Once you have final values for each street, the last step is making the map. It can look like whatever you determine is a clear way to represent the cycling environment. Here is one possibility:
This blog post does not present a completed example. Instead, it builds out a (thought) process. The goals of this process are to more holistically represent street conditions for cycling, build a collective understanding around what constitutes a pleasant bicycling environment, and then make the cycling environment more transparent and understandable to the wider public.