Mapping complexity

Our studio instructor posed a question to our class: “Which is better: Ian McHarg’s layer cake approach to mapping, or illustrative, storytelling mapping?” This question doesn’t necessarily set up a dichotomy but rather points out that there is not a best approach, to anything.

I appreciated this new (to me) view that McHarg — in an effort to address the complexities of ecological systems — siloed off elements that are inherently linked to one another. Until now, I’d only seen the layer cake attempt at addressing complexity as “good.” But of course it’s not perfect. There is no singular, perfect way of approaching the world, or making universally beneficial decisions. I think there is infinite work we could do better, so this is absolutely not an excuse for not trying. But it’s a reason for multiplicity of solutions!

Ian McHarg, landscape architect and founder of University of Pennsylvania’s landscape architecture department, is an icon for his work with ecological systems their inherent complexities. The “layer cake” model is a form of suitability analysis, that overlays multiple, independent sets of data with the goal of revealing the most suitable areas for development. This approach opened the door for digitizing spatial data and making sense of complexity in a way we hadn’t yet (geographic information systems), and it set a new bar for addressing complexity. But as usually happens (in a world driven by capitalism, at least) we stall out after a new bar is set, using it as a baseline achievement with rare effort to move beyond. The layer cake approach is also very indicative of some of our real tendencies to silo and separate, put in place.

Ian McHarg’s “Physiographic Obstructions,” Design with Nature (1969) link to image

And maybe — especially as we are learning these new ideas and their potential — we forget that even McHarg’s suitability analysis tells a story, whether explicit or not. Maps can communicate infinite types of information, so we have to make choices about what is communicated and what is not. In the case of a suitability analysis, someone has to choose which layers are represented in the analysis and what these layers mean. Just because they are based in quantifiable data does not mean that they are unequivocally true. In fact, the data-ization of these complexities might remove the burden of personal, moral responsibility that comes with major planning decisions.

It’s critical that we know stories can be communicated in many ways, that we may or may not even notice when stories are being told, that stories are embedded in “objective reality.” Our recent discussions about scale, infrastructure, and armatures — what we see and what we take as truth — reminded me of a moment of illumination in college. A friend described to me the agency we give to sperm and the passivity we apply to the egg in the classic sex ed narrative. Maybe it’s obvious to many, but for me it’s a strong example of how invisible the stories of “science” can be. Of course, the sperm/egg story is a mild example of the ways that people have employed science to legitimize cruelty, but it is an anecdote that pushed me to realize that I myself had been snowed.

But storytelling is a very legitimate way for us to understand place, and it can be one of the best ways to communicate with one another. Though our minds can comprehend space and directions from above, like a traditional map, we also understand space from our own human-scale, turn-by-turn perspective. Recently, Google made a change in its mapping software that acknowledged this truth. In addition to traditional GPS directions, Google incorporated a form of storytelling, referring to local landmarks to direct users to their destinations. The new Google maps say, for instance “turn left at Taco Bell,” which makes their directions a bit more narrative, more connected to the experience of a place, with a higher resolution of understanding.

The places we will be helping to build as landscape architects will inevitably become regular parts of many peoples’ lives, whether by choice, necessity, or randomness. And we will be doing a lot of mapping in our attempts to understand new geographies — when planning out projects and trying to make decisions that successfully support complexity. It’s impossible that either of the two approaches above are the best way to map and comprehend place, since there is not a best way. Maybe the most reliable approach is to be willing to do things differently each time, to be adaptable and open-minded and acknowledge that there is more we do not know.