Equitable Access to Potential Parks (Southeast Blueprint Indicator ) [U.S. Fish and Wildlife Service] {2023} Full Details

Full Details

Title:

Equitable Access to Potential Parks (Southeast Blueprint Indicator ) [U.S. Fish and Wildlife Service] {2023}

Description:

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 The Trust for Public Land (TPL) ParkServe database, accessed 8-8-2021: Park priority areas (ParkServe_ParkPriorityAreas_08062021) From the TPL ParkServe documentation: The ParkServe database maintains an inventory of parks for every urban area in the U.S., including Puerto Rico. This includes all incorporated and Census-designated places that lie within any of the country's 3,000+ census-designated urban 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:Population densityDensity of low-income households - which are defined as households with income less than 75 percent of the urban area median household incomeDensity of people of colorCommunity health - a combined index based on the rate of poor mental health and low physical activity from the 2020 CDC PLACES census tract datasetUrban heat islands - surface temperature at least 1.25o greater than city mean surface temperature from The Trust for Public Land, based on Landsat 8 satellite imageryPollution burden - Air toxics respiratory hazard index from 2020 EPA EJScreen The 10-minute walkFor 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. 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.... 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). Base Blueprint 2022 extent Southeast Blueprint 2023 extent Mapping Steps Convert the ParkServe park priority areas 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 more equity into this indicator, we also use the CDC Social Vulnerability Index to narrow down the results. Reclassify the ParkServe raster to make NoData values 0. 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 the 4 classes seen in the final indicator below. Clip to the spatial extent of Base Blueprint 2022. As a final step, clip to the spatial extent of Southeast Blueprint 2023. Note: For more details on the mapping steps, code used to create this layer is available in theSoutheast Blueprint Data Downloadunder > 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 access1 = Moderate priority for a new park that would create nearby equitable access 0 = Not identified as a priority for a new park that would create nearby equitable access (within urban areas) 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. This indicator underestimates places in rural areas where many people within a socially vulnerable census tract would benefit from a new park. ParkServe covers incorporated and Census-designated places within census-designated urban areas, 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. Other Things to Keep in MindThe zero values in this indicator contain three distinct types of areas that we were unable to distinguish between in the legend: 1) Areas that are not in a community analyzed by ParkServe (ParkServe covers incorporated and Census-designated places within census-designated urban areas); 2) Areas in a community analyzed by ParkServe that were not identified as a priority; 3) Areas that ParkServe identifies as a priority but do not meet the SVI threshold used to represent areas in most need of improved equitable access.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(NRPA 2021, Manuel-Navarete et al. 2004).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, asit 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. 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.ncbi.nlm.nih.gov/pmc/articles/PMC7179070/]. Gies E. (2006). The health benefits of parks: how parks help keep Americans fit & healthy. The Trust for Public Land. Accessed February 16, 2022. [https://cloud.tpl.org/pubs/benefits_HealthBenefitsReport.pdf]. 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. [https://link.springer.com/article/10.1007/s11252-016-0586-5]. 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. [https://link.springer.com/article/10.1007/s11252-019-00890-6]. Manuel-Navarrete D, Kay JJ, Dolderman D. Ecological integrity discourses: linking ecology with cultural transformation. Human Ecology Review 2004, 11:215-229. [https://www.jstor.org/stable/24707715]. National Recreation and Park Association. "NRPA Park Metrics." 2021. Accessed April 5, 2021. [https://www.nrpa.org/publications-research/research-papers/agency-performance-review/]. Simpson, J. R. (1998). Urban forest impacts on regional cooling and heating energy use: Sacramento County case study. Journal of Arboriculture, 24, 201-214. [https://www.fs.usda.gov/research/treesearch/61731]. 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]. 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].

Creator:

Department of the Interior

Provider:

U.S. Fish and Wildlife Service Open Data

Resource Class:

Imagery and Web services

Temporal Coverage:

2023

Date Issued:

2023-09-25

Place:

United States

Rights:

The United States Fish and Wildlife Service (Service) shall not be held liable for improper or incorrect use of the data described and/or contained herein. While the Service makes every reasonable effort to ensure the accuracy and completeness of data provided for distribution, it may not have the necessary accuracy or completeness required for every possible intended use. The Service recommends that data users consult the associated metadata record to understand the quality and possible limitations of the data. The Service creates metadata records in accordance with the standards endorsed by the Federal Geographic Data Committee. As a result of the above considerations, the Service gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of the data. It is the responsibility of the data user to use the data in a manner consistent with the limitations of geospatial data in general and these data in particular. Although these data have been processed successfully on a computer system at the Service, no warranty, expressed or implied, is made regarding the utility of the data on another system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. This applies to the use of the data both alone and in aggregate with other data and information.

Access Rights:

Public

Format:

Imagery

Language:

English

Date Added:

2023-10-17