Over the past year, our research team has continued to deepen our understanding of equitable access to parks. The pandemic has reinforced the importance of walkable access to quality open spaces and shed further light on the unfair disparities in access in many communities.

We have focused this year on mapping access disparities, highlighting areas within communities that are statistically over-served or underserved for park acreage per capita and analyzing who lives in these areas. Analyzing park access in 19 cities, we have found significant disparities in access along racial/ethnic lines. We are now comparing these patterns to historic park system design, former redlined areas (1), and current trends in neighborhood change (2), including both growing areas of concentrated poverty to zones of gentrification and displacement. We are seeking to illuminate who is enjoying great park access and who is disproportionately left out, while also studying the origins of these trends and ongoing contributing factors.

A few snapshots of our in-progress research follow.

High and Low Access Areas

In many cities, races/ethnicities who disproportionately live more often in high access areas are also living less often in low access areas, exacerbating disparities in park access. For example, in Minneapolis and Buffalo, white residents are over-represented in high park access areas by 14% and 43% respectively, and under-represented in low park access areas (-18% and -22%). Meanwhile, the opposite is true for black residents in both cities, who live less often in high park access areas (-15% and -63%) and more often in low park access areas (+26% and +37%). Similar patterns exist in 60% of the 19 cities we studied.

Methodology

1. Map areas of statistically high and low access within each city. Park access is defined as park acreage/capita calculated by looking at the population within a 10 minute walk and the size of the park. It also takes into account if a Census Block is within a 10 minute walk of multiple parks.
2. Quantify the number of residents of each race/ethnicity living in high and low access areas.
3. Compare this to the number of residents expected to live in high and low access areas if the high and low access areas had the same population distribution as the city as a whole. Calculate the percent difference in expected and observed for each race/ethnicity. For example, in New Orleans, 55% of residents living in high park access areas are white, compared to only 32% of the citywide population. This difference is 70% more white residents living in high access areas than would be expected based on the citywide population (3).

1. Data source: Mapping Inequality, a collaboration of research teams, professors, and students from the University of Richmond, Virginia Tech, University of Maryland, and Johns Hopkins University. https://dsl.richmond.edu/panorama/redlining/#loc=5/39.1/-94.58
2. Data source: Neighborhood Change in the 21st Century. University of Minnesota – Institute on Metropolitan Opportunity. https://myottetm.github.io/USMapBoxIMO/USLwDispConc.html and https://www.law.umn.edu/gentrification-and-decline-about-web-map-data
3. Data sources: ACS 5-year estimates (2013-2017), Decennial Census 2010, TPL ParkServe national database of parks, and Sasaki geospatial analysis of areas within each city with statistically high park acreage and low park acreage.

Research team: Jill Allen Dixon, Kai Ying Lau, Elaine Minjy Limmer, Laura Marett, Raj Adi Raman, Ken Goulding, Anastasia Lyons