Equitable Access to Potential Parks

This cultural resource indicator prioritizes places to create new parks that would fill gaps in equitable access to open space within socially vulnerable communities. It identifies areas where residents currently lack access to parks within a 10-minute walk (accounting for walkable road networks and access barriers like highways and fences), then prioritizes based on park need using demographic and environmental metrics. This indicator originates from the Trust for Public Land’s ParkServe park priority areas.

Reason for Selection

Protected natural areas help foster a conservation ethic by providing opportunities for people to connect with nature, and also support ecosystem services like offsetting heat island effects (Greene and Millward, 2017, Simpson, 1998), water filtration, stormwater retention, and more (Hoover and Hopton, 2019). In addition, parks, greenspace, and greenways can help improve physical and psychological health in communities (Gies, 2006). However, parks are not equitably distributed within easy walking distance for everyone. This indicator aligns with Executive Order 14008, which calls for a greater focus on environmental justice and equity, as well as public health, land and water conservation, and climate change resilience. It also complements the urban park size indicator by capturing the value of potential new parks.

Input Data

• 2019 National Land Cover Database (NLCD)
• Base Blueprint 2022 extent

• CDC Social Vulnerability Index 2018: RPL_Themes

  Social vulnerability refers to the capacity for a person or group to “anticipate, cope with, resist and recover from the impact” of a natural or anthropogenic disaster such as extreme weather events, oil spills, earthquakes, and fires. Socially vulnerable populations are more likely to be disproportionately affected by emergencies (Wolkin et al. 2018).

  In this indicator, we use the “RPL_THEMES” attribute from the Social Vulnerability Index, described here. “The Geospatial Research, Analysis, and Services Program (GRASP) at Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry developed the Social Vulnerability Index (SVI). The SVI is a dataset intended to help state, local, and tribal disaster management officials identify where the most socially vulnerable populations occur (Agency for Toxic Substances and Disease Registry [ATSDR], 2018)” (Flanagan et al. 2018).

  “The SVI database is regularly updated and includes 15 census variables (ATSDR, 2018). Each census variable was ranked from highest to lowest vulnerability across all census tracts in the nation with a nonzero population. A percentile rank was calculated for each census tract for each variable. The variables were then grouped among four themes (Figure 1). A tract-level percentile rank was also calculated for each of the four themes. Finally, an overall percentile rank for each tract as the sum of all variable rankings was calculated. This process of percentile ranking was then repeated for the individual states” (Flanagan et al. 2018).

• The Trust for Public Land (TPL) ParkServe Data, accessed 8-8-2021: ParkServe_ParkPriorityAreas_08062021

  From the TPL ParkServe documentation:

  The 10-minute walk

  For each park, we create a 10-minute walkable service area using a nationwide walkable road network dataset provided by Esri. The analysis identifies physical barriers such as highways, train tracks, and rivers without bridges and chooses routes without barriers.

  Park priority areas

  All populated areas in a city that fall outside of a 10-minute walk service area are assigned a level of park priority, based on a comprehensive index of six equally weighted demographic and environmental metrics (* indicates based on 2020 U.S. block groups provided by Esri):

  • Population density*
  • Density of low-income households* - which are defined as households with income less than 75 percent of the urban area median household income
  • Density of people of color*
  • Community health - a combined index based on the rate of poor mental health and low physical activity from the 2020 CDC PLACES census tract dataset
  • Urban heat islands - surface temperature at least 1.25^o greater than city mean surface temperature from The Trust for Public Land, based on Landsat 8 satellite imagery
  • Pollution burden - Air toxics respiratory hazard index from 2020 EPA EJScreen

Mapping Steps

• Convert the ParkServe Park Priority Layer to a raster using the ParkRank field. Note: The ParkRank scores are calculated using metrics classified relative to each city. Each city contains park rank values that range from 1-3. For the purposes of this indicator, we chose to target potential park areas to improve equity. Because the ParkRank scores are relative for each city, a high score in one city is not necessarily comparable to a high score from another city. In an effort to try to bring in more equity to this indicator, we also use the CDC Social Vulnerability Index to narrow down the results.Convert the SVI layer from vector to raster based on the “RPL_Themes” field.
• To limit the ParkRank layer to areas with high SVI scores, first identify census tracts with an “RPL_Themes” field value >0.65. Make a new raster that assigns a value of 1 to census tracts that score >0.65, and a value of 0 to everything else. Take the resulting raster times the ParkRank layer.
• Reclassify this raster into 3 classes, seen in the final indicator below.
• As a final step, clip to the spatial extent of Base Blueprint 2022.

Note: For more details on the mapping steps, code used to create this layer is available in the Southeast Blueprint 2022 Data Download under BlueprintInputs > BaseBlueprint2022 > 6_Code.

Final Indicator Values

Indicator values are assigned as follows:

• 3 = Very high priority for a new park that would create nearby equitable access
• 2 = High priority for a new park that would create nearby equitable access
• 1 = Moderate priority for a new park that would create nearby equitable access

Known Issues

• This indicator could overestimate park need in areas where existing parks are missing from the ParkServe database. TPL regularly updates ParkServe to incorporate the best available park data. If you notice missing parks or errors in the park boundaries or attributes, you can submit corrections through the ParkReviewer tool or by contacting TPL staff.
• Within a given area of high park need, the number of people served by the creation of a new park depends on its size and how centrally located it is. This indicator does not account for this variability. Similarly, while creating a new park just outside an area of high park need would create access for some people on the edge, the indicator does not capture the benefits of new parks immediately adjacent to high-need areas. For a more granular analysis of new park benefits, ParkServe’s ParkEvaluator tool allows you to draw a new park, view its resulting 10-minute walk service area, and calculate who would benefit.
• Beyond considering distance to a park and whether it is open to the public, this indicator does not account for other factors that might limit park access, such as park amenities or public safety. The TPL analysis excludes private or exclusive parks that restrict access to only certain individuals (e.g., parks in gated communities, fee-based sites). The TPL data includes a wide variety of parks, trails, and open space as long as there is no barrier to entry for any portion of the population.
• The indicator does not incorporate inequities in access to larger versus smaller parks. In predicting where new parks would benefit nearby people who currently lack access, this indicator treats all existing parks equally.
• This indicator identifies areas where parks are needed, but does not consider whether a site is available to become a park. We included areas of low intensity development in order to capture vacant lots, which can serve as new park opportunities. However, as a result, this indicator also captures some areas that are already used for another purpose (e.g., houses, cemeteries, and businesses) and are unlikely to become parks. In future updates, we would like to use spatial data depicting vacant lots to identify more feasible park opportunities.
• Some areas identified in this indicator are not eligible to be prioritized in the final Blueprint. When we perform the optimization process in Zonation, we remove areas in the NLCD high and medium intensity development classes (see the Running Zonation section). Ideally, we would leave in the medium density development class, as it includes more vacant areas that could serve as potential parks. The NLCD medium intensity development class is defined as areas with a mixture of constructed materials and vegetation, where impervious surfaces account for 50% to 79% of the total cover. These areas most commonly include single-family housing units. We are working on new methods that will allow us to include these areas in future Blueprint updates.
• This indicator underestimates places in rural areas where many people within a socially vulnerable census tract would benefit from a new park. ParkServe assesses almost 14,000 cities, towns and communities across the United States that fall within or touch a census-designated urban area, which leaves out many rural areas. We acknowledge that there are still highly socially vulnerable communities in rural areas that would benefit from the development of new parks. However, based on the source data, we were not able to capture those places in this version of the indicator.
• This indicator only includes park priority areas that fall within the 65th percentile or above from the Social Vulnerability Index. We did not perform outreach to community leaders or community-led organizations for feedback on this threshold.
• This indicator is intended to generally help identify potential parks that can increase equitable access, but should not be solely used to inform the creation of new parks. As the social equity component relies on information summarized by census tract, it should only be used in conjunction with local knowledge and in discussion with local communities.

Disclaimer: Comparing with Older Indicator Versions

There are numerous problems with using Southeast Blueprint indicators for change analysis. Please consult Blueprint staff if you would like to do this (email hilary_morris@fws.gov).

Literature Cited

Centers for Disease Control and Prevention/ Agency for Toxic Substances and Disease Registry/ Geospatial Research, Analysis, and Services Program. CDC/ATSDR Social Vulnerability Index [2018] Database [US]. [https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html].

Flanagan BE, Hallisey EJ, Adams E, Lavery A. Measuring Community Vulnerability to Natural and Anthropogenic Hazards: The Centers for Disease Control and Prevention’s Social Vulnerability Index. J Environ Health. 2018;80(10):34-36. [https://www.neha.org/sites/default/files/jeh/JEH6.18-Column-Direct-From-ATSDR.pdf].

Gies E. (2006). The health benefits of parks: how parks help keep American’s fit & healthy. The Trust for Public Land [http://cloud.tpl.org/pubs/benefits_HealthBenefitsReport.pdf]. Accessed February 16, 2022.

Greene, C. S., & Millward, A. A. (2017). Getting closure: The role of urban forest canopy density in moderating summer surface temperatures in a large city. Urban ecosystems, 20(1), 141-156.

Hoover, F. A., & Hopton, M. E. (2019). Developing a framework for stormwater management: leveraging ancillary benefits from urban greenspace. Urban ecosystems, 22(6), 1139-1148.

Manuel-Navarrete D, Kay JJ, Dolderman D. Ecological integrity discourses: linking ecology with cultural transformation. Human Ecology Review 2004, 11:215–229.

National Recreation and Park Association. “NRPA Park Metrics.” 2021. Accessed April 5, 2021. [https://www.nrpa.org/publications-research/ParkMetrics/].

Simpson, J. R. (1998). Urban forest impacts on regional cooling and heating energy use: Sacramento County case study. Journal of Arboriculture, 24, 201-214.

U.S. Geological Survey (USGS). Published June 2021. National Land Cover Database (NLCD) 2019 Land Cover Conterminous United States. Sioux Falls, SD. [https://doi.org/10.5066/P9KZCM54].

Warnell, K. 2020. Conservation Priorities for Open Space Recreation Access: U.S. Geological Survey ScienceBase. [https://doi.org/10.21429/k9k5-fz91].

Wolkin A, Patterson JR, Harris S, et al. Reducing Public Health Risk During Disasters: Identifying Social Vulnerabilities. J Homel Secur Emerg Manag. 2015;12(4):809-822. [https://doi.org/10.1515/jhsem-2014-0104].

Yang, L., Jin, S., Danielson, P., Homer, C., Gass, L., Case, A., Costello, C., Dewitz, J., Fry, J., Funk, M., Grannemann, B., Rigge, M. and G. Xian. 2018. A New Generation of the United States National Land Cover Database: Requirements, Research Priorities, Design, and Implementation Strategies, ISPRS Journal of Photogrammetry and Remote Sensing, 146, pp.108-123. [https://doi.org/10.1016/j.isprsjprs.2018.09.006].