Empirical Measures of Park Use in American Cities, and the Demographic Biases of Spatial Models

24 Pages Posted: 20 Dec 2019

See all articles by James Saxon

James Saxon

University of Chicago / Center for Data and Computing

Date Written: December 12, 2019

Abstract

City planners have a professional and ethical responsibility to provide public goods equitably. Parks improve mental and physical health by nurturing social cohesion and enabling physical activity. So who gets parks? Park access has traditionally been evaluated using constructed variables of potential access: distance buffers or gravity models. These models have major limitations: they ignore commutes and other more intricate mobility behaviors. To address these issues, I propose a nationally scalable,empirical measure of realized use. Using a dataset of smartphone locations, I identify visits to parks in the twenty largest American cities. I use these data to calibrate existing models, and then contrast the models with realized use. The traditional models are not simply imprecise; they systematically over-estimate realized access by minority populations. In other words, they understate inequity. On the other hand,the new data come with substantial challenges. They are a convenience sample, biased towards wealthier,whiter populations. While these biases appear to be moderate, continued work with these and similar data will require continued attention to the sample frame.

Keywords: parks, smartphones, neighborhood, gps, accessibility

JEL Classification: R23, C55

Suggested Citation

Saxon, James, Empirical Measures of Park Use in American Cities, and the Demographic Biases of Spatial Models (December 12, 2019). Mansueto Institute for Urban Innovation Research Paper , Available at SSRN: https://ssrn.com/abstract=3502949 or http://dx.doi.org/10.2139/ssrn.3502949

James Saxon (Contact Author)

University of Chicago / Center for Data and Computing ( email )

Chicago, IL
United States

HOME PAGE: http://saxon.cdac.uchicago.edu

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
254
Abstract Views
1,292
Rank
240,960
PlumX Metrics