Arc-GIS Online Map of 405 and McDonald’s Restaurants
September 29, 2019
For my Arc-GIS Online Map, I decided to map my usual freeway route on the 405 when traveling between West Los Angeles and Chapman University by utilizing the live traffic layer that reports stoppages, delays, and slowdowns in real time. I began the 405 driving route from a restaurant called Hamburger Habit, which is one of those family owned fast food places that have been advertised throughout Los Angeles since the late eighties. Here is the legendary advertisement that still plays on television sets throughout Los Angeles to this day:
I chose the Hamburger Habit as a starting point because it’s iconic of its proximity to the Overland 405 Exit, which is known as one of most congested exits on that freeway (Joan Didion even mentioned the Overland Exit in The WhiteAlbum). And while traffic is a typical factor when driving on the 405, I also decided to explore the frequency of every McDonald’s fast food restaurant throughout that area. I was lucky to have found a data set layer from some pour soul who input every McDonald’s location in the country. I decided to measure McDonald’s since the restaurant is understood as a ubiquitous, corporate fast food chain with a unique connotation of social class imposed onto its customers. Likewise, as the clusters of McDonald’s restaurants appeared, I noticed that certain areas throughout the Los Angeles map seemed to have a larger cluster of McDonald’s than others areas. This led me to eventually use a map layer that displays the median household income of the LA area within 2019. The overlapping results were interesting:
My map shows that McDonald’s seemed to concentrate in those areas that have a lower household income, which also corresponds to each areas proximity to the freeway. On my map, I pinpointed 9 locations of interest that show an interesting overlap and a moment of interpretation. For example, point 4 on the map falls at an intersection of two freeways, is near a white zone of household income (which signifies an area with a median household income of less than $14,700), and contains at least 3 McDonald’s in its 5 mile radius. These overlaps fascinate me, especially regarding the location of the 405 in accordance to these areas of varying household incomes. For me, my map reveals how the 405 implies an overall effect to its surrounding areas, even when drivers like me don’t spend much time in those areas except as passing commuters or as prisoners stuck in traffic.
However, regarding the actual spatialization of data like traffic, median household income, and McDonald’s locations, these maps don’t necessarily show the emotion, or as Johanna Drucker coins, the capta, regarding those interpretable points. It may be easy to measure where cars slow down on the 405, but after reading Drucker’s article, I keep am asking myself the same questions: How would one show the feeling of being stuck in traffic? What about showing one’s perception of time on the freeway? How would one map the feelings of hunger, then interpret the intensity of those emotions in relation to location and the varying household incomes? And, most importantly, how could you show these capta in a multi-faceted, transformative, and impactful way to the viewer? As Drucker exposits, “Plans change, travel times are altered, arrivals and departures re-arranged, moods shift, frustrations intensify, disappointments or unexpected surprises arise in relation to the sequence of events. An email recounting something that occurred “yesterday” in relation to a date stamp might also contain more vaguely identified “earlier” and “before” statements that put events into a relative sequence without explicitly identifying when these occurred. As the telling unfolds, these relations may change in the writer’s expression and perception, so that the textual description of a recollected event continues to shift its place in the temporal order” (Drucker 45). While I do feel that the live feature of the Arc-GIS map, as well as its interactive and malleable online format, are able to compensate with these shifting capta, I feel that to graph them with a fluid and dynamic spatialization would leave the viewer with a larger impact and interpretative understanding of the area.