Month: November 2018

Exploring LA’s Restaurant Niches

LA’s Mexican and Chinese Restaurant Niches

A niche, as Popielarz and Neal say in their 2007 article is a set of environmental conditions under which a species thrives. As part of the Urban Genome Project, we are searching for the characteristics of ‘niches’ that allow for urban forms to reproduce, and how these characteristics may have changed over time. Here, we demonstrate our approach by applying the niche concept to Los Angeles’ restaurant scene. Stay tuned for more detailed studies. 

These maps show the neighborhoods with and without Mexcian and Chinese Restaurants. Red-shaded zip codes have restaurants of a certain type, dark ones do not. Given the abundance of these restaurants forms in LA as a whole, it’s reasonable to conclude that most black-shaded areas do not have the conditions required to sustain a certain restaurant species. 

Data for the maps comes from recent Yellow Pages directories, generously shared with us by the “friendly cities lab”. It may not be fully representative of all restaurants but there’s no reason to believe that it is biased.

According to this data:

  • Nearly half of all zip codes with restaurants have both Chinese and Mexican restaurants, 19% just have Mexican restaurants and  17% just have Chinese.
  • There is only a loose correlation betweeen the number of Chinese and Mexican restaurants in a zip code(r=.16)
  • 56% of ‘Chinese-Only’ niches are in LA City but only 32% of Mexican Only ones are.
  • Long Beach, East Los Angeles, and Santa Clarita stand out as cities with more Chinese restaurant deserts; Glendale stands out as a city with more Chinese Restaurant Deserts.  

You can explore the trends with the maps pasted below, or at the app here.

Mexican Restaurant Niches

Map by Fabio Dias

Chinese Restaurant Niches

Map by Fabio Dias

Piccard: Workshop material and cross city comparison


Mapping the evolution of cities

The project workshop on Nov 2, 2018 includes a presentation about Piccard and related efforts to understand urban data.

The presentation can be found here .

Related internal resources: