Zachary Elliott


Design Projects

  1. Embracing the Ruin
  2. A Torrington Square Adventure


Design Research

  1. Encountering the Riverine Park Nexus
  2. Green Space in Denver
  3. Molten Wastelands


Photography

  1. Architecture
  2. Landscape
  3. Urban


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MLA Landscape Architecture at The Bartlett                    BA Geography (First Class) at Oxford                        Freelance Photographer                    

© Zachary Elliott 2024

Green Space in Denver


BA Geography / Geographic Data Science Final Project


Introduction

Residential access to public green space has been linked to improved physical health, lower levels of stress, increased mental wellbeing, cooler urban climates, and increased urban biodiversity levels (Bolund and Hunhammar, 1999; Fuller et al., 2007; Bowler et al., 2010; Ward Thompson et al., 2012; Hartig et al., 2014; Markevych et al., 2017).

However, green space is not evenly distributed in cities like Denver (Burgess et al., 1988; Wang et al., 2015). Access to green space is a social justice issue as a vital contributor to good health (Maller et al., 2006).
 
This research project deploys counter-mapping practices and geospatial techniques to examine the uneven provision of green spaces in the Denver-Aurora-Lakewood conurbation. It asks “which areas of Denver-Aurora-Lakewood have the best and worst provision of green spaces within a 10-minute walk of residential addresses?” and “where in Denver-Aurora-Lakewood is in most need of macro-scale green space interventions”? Green spaces are defined as formal parks and nature reserves, macro-scale green space interventions that act as destinations for urbanites to have contact with nature.





Green Space Provision in Denver-Aurora

The analysis presented in this research project demonstrates that green space provision in the Denver-Aurora-Lakewood conurbation continues to be highly stratified along axes of race and income. Lower-income and predominantly Black and Latino neighbourhoods in Aurora and North Denver are particularly poorly served by public green spaces, with less than 10% of residential properties being able to access a park within a 10-minute walk of home in many cases (Maps 5-8). When these parks do exist, they are often poor quality and small in size (Maps 3 & 4). This is a legacy of systematic disinvestment in these neighbourhoods.

It is important to contextualise metrics of greenspace accessibility with socioeconomic data, as predominantly white and wealthy neighbourhoods in Denver-Aurora-Lakewood have poor access to public green space compensated by high levels of access to private green spaces (Maps 1, 3, 5 & 6).
Policy Recommendations

This project recommends that green space investments should be considered in Aurora and North Denver to counteract long-term and racialised systematic disinvestment in these neighbourhoods through practices of redlining and discriminatory urban planning. People living in these neighbourhoods do not only have low levels of residential park access relative to the rest of the conurbation (Maps 5-8) but are also exposed to high levels of environmental hazards, which green space interventions could work to ameliorate. Green spaces reduce harms to health by cooling the neighbourhoods around them and by offering a sanctuary from the noise and pollution of the city to the urbanites who use them. 

North Denver experiences high levels of Heat Severity in almost all neighbourhoods, while other neighbourhoods have only patches of heat severity, even if more extreme (Map 9). This means that there is almost no space to seek respite from the heat for residents in these neighbourhoods.

Furthermore, both Aurora and North Denver experience very high levels of transportation noise (Map 10) relative to the rest of the conurbation, as highways run past and through many lower-income, Black, and Latino neighbourhoods in the urban area. These noise inequalities are a product of the systematic allocation of disposability along lines of race and income that characterises much of America’s post-war freeway planning. This is accentuated by how North Denver and Aurora experience higher levels of pollution than some of the wealthier suburbs in the South of the city (Map 11), in part because more cars and highways run through these neighbourhoods than in other parts of the conurbation.

Where green space needs to be created in Denver-Aurora-Lakewood is clear. The question is now how more green space can be provided in Aurora and North Denver without the displacement of existing populations through processes of green gentrification (Safransky, 2014; Anguelovski et al., 2019; Penney, 2020).




Methods

To identify which areas of Denver-Aurora-Lakewood have the best and worst provision of green spaces within a 10-minute walk of residential addresses, a network model was built using OpenStreetMap (OSM) Road and Path line data to compute service areas for all entrances to urban green spaces (parks and nature reserves) in Denver-Aurora-Lakewood. These service area walksheds were then used to assign the time taken to walk to an urban park entrance to each residential address in Denver-Aurora-Lakewood. This data was generalised to the Census Block Group level, as a proportion of residential addresses in each block group that can access a park within a 10-minute walking distance. This was compared with socio-economic and environmental data to make subjective judgements on where in Denver-Aurora-Lakewood is most in need of macro-scale green space interventions. A 10-minute walking distance (half a mile) is generally considered to be the furthest people are willing to regularly walk to access a green space (Wolch et al., 2005; Boone et al., 2009; Rigolon, 2017).

The network approach to calculating the service areas of urban green spaces was selected over a straight-line radius approach. A straight-line radius, or buffer, approach to calculating the service areas of urban parks does not consider the positions of a park’s point(s) of access and does not realistically account for the real distance taken by park users to access a park, as it assumes that movement is free and possible in all directions (Figure 1). A network approach more closely emulates the actual routes that users are likely to follow between residential addresses and points of access to urban parks by measuring distance along roads and public rights of way to parks rather than in a straight line (Nicholls, 2001). Figure 1 makes this clear.


Figure 1 Using a straight-line radius approach, the walking distance between House B and the park is treated as shorter than the distance between House A and the park. The network model approach more closely emulates the reality of suburban areas, where it takes much longer to walk from House B to the park than from House A to the park because the park user living in House B must exit their housing estate, walk along the sidewalk by a major road, and then walk along House A’s road to access the park.





Bibliography

Bolund, P. and Hunhammar, S. (1999) ‘Ecosystem services in urban areas’, Ecological Economics, 29(2), pp. 293–301. doi:10.1016/S0921-8009(99)00013-0.

Boone, C.G. et al. (2009) ‘Parks and People: An Environmental Justice Inquiry in Baltimore, Maryland’, Annals of the Association of American Geographers, 99(4), pp. 767–787. doi:10.1080/00045600903102949.

Bowler, D.E. et al. (2010) ‘Urban greening to cool towns and cities: A systematic review of the empirical evidence’, Landscape and Urban Planning, 97(3), pp. 147–155. doi:10.1016/j.landurbplan.2010.05.006.

Burgess, J. et al. (1988) ‘People, Parks and the Urban Green: A Study of Popular Meanings and Values for Open Spaces in the City’, Urban Studies, 25(6), pp. 455–473. doi:10.1080/00420988820080631.

Fuller, R.A. et al. (2007) ‘Psychological benefits of greenspace increase with biodiversity’, Biology Letters, 3(4), pp. 390–394. doi:10.1098/rsbl.2007.0149.

Hartig, T. et al. (2014) ‘Nature and Health’, Annual Review of Public Health, 35(1), pp. 207–228. doi:10.1146/annurev-publhealth-032013-182443.

Maller, C. et al. (2006) ‘Healthy nature healthy people: “contact with nature” as an upstream health promotion intervention for populations’, Health Promotion International, 21(1), pp. 45–54. doi:10.1093/heapro/dai032.

Markevych, I. et al. (2017) ‘Exploring pathways linking greenspace to health: Theoretical and methodological guidance’, Environmental Research, 158(June), pp. 301–317. doi:10.1016/j.envres.2017.06.028.

Nicholls, S. (2001) ‘Measuring the accessibility and equity of public parks: a case study using GIS’, Managing Leisure, 6(4), pp. 201–219. doi:10.1080/13606710110084651.

Penney, V. (2020) ‘Denver Wants to Fix a Legacy of Environmental Racism’, The New York Times, 30 September. Available at: https://www.nytimes.com/2020/09/30/climate/city-parks.html (Accessed: 24 April 2022).

Rigolon, A. (2017) ‘Parks and young people: An environmental justice study of park proximity, acreage, and quality in Denver, Colorado’, Landscape and Urban Planning, 165, pp. 73–83. doi:10.1016/j.landurbplan.2017.05.007.

Safransky, S. (2014) ‘Greening the urban frontier: Race, property, and resettlement in Detroit’, Geoforum, 56, pp. 237–248. doi:10.1016/j.geoforum.2014.06.003.

Wang, D. et al. (2015) ‘The physical and non-physical factors that influence perceived access to urban parks’, Landscape and Urban Planning, 133, pp. 53–66. doi:10.1016/j.landurbplan.2014.09.007.

Ward Thompson, C. et al. (2012) ‘More green space is linked to less stress in deprived communities: Evidence from salivary cortisol patterns’, Landscape and Urban Planning, 105(3), pp. 221–229. doi:10.1016/j.landurbplan.2011.12.015.

Wolch, J. et al. (2005) ‘Parks and Park Funding in Los Angeles: An Equity-Mapping Analysis’, Urban Geography, 26(1), pp. 4–35. doi:10.2747/0272-3638.26.1.4.

Wolch, J.R. et al. (2014) ‘Urban green space, public health, and environmental justice: The challenge of making cities “just green enough”’, Landscape and Urban Planning, 125, pp. 234–244. doi:10.1016/j.landurbplan.2014.01.017.
Data Sources

[1]    Adams County Colorado Government – Zoning. Data available at https://data-adcogov.opendata.arcgis.com/datasets/f4060f8fb08742c797a3a2d8d456ca03_0/about and under a Creative Commons Attribution 4.0 International License. Zone district regulations are listed at https://www.adcogov.org/sites/default/files/Chapter 03 - Zone District Regulations_0.pdf
[2]    Broomfield County – Addresses. Data available at https://opendata.broomfield.org/datasets/2aa832f778224f068b9f271b1d3e5e0f_0/about
[3]    City of Arvada – Zoning. Data available at https://gis-arvada.opendata.arcgis.com/datasets/557477077d2b4b728e1f4dbae7e334f8_0/about
[4]    City of Aurora – Buildings, Esri Community Maps Contributors; Aurora, CO; CC BY 4.0. Data available at https://services6.arcgis.com/Do88DoK2xjTUCXd1/arcgis/rest/services/Aurora_CO_Buildings/FeatureServer
[5]    City of Brighton – Zoning. Data available at https://brighton.maps.arcgis.com/home/item.html?id=0801681127324cd38b982a65da273dd4
[6]    City of Federal Heights – Zoning. Data available at https://www.fedheights.org/index.asp?SEC=D1A883BE-0C29-4602-8CC9-5D6A08DA5503
[7]    City of Northglenn – Zoning. Data available at https://services7.arcgis.com/JeS0Sns8Qnvm0GB9/arcgis/rest/services/NorthglennZoning/FeatureServer
[8]    City of Thornton – Addresses. Data available at https://data-cityofthornton.opendata.arcgis.com/datasets/cityofthornton::addresses-for-download/about
[9]    City of Westminster – Residential Area Boundaries. Data available at https://services1.arcgis.com/1qGtTVx4f5UwkUd6/arcgis/rest/services/Residential_Boundary/FeatureServer
[10]    Commerce City – Addresses. Data available at https://data-c3.opendata.arcgis.com/datasets/addresses-1
[11]    ESRI Living Atlas – 2021 Population Density by Block Group. Accessed through the Enrich Geoprocessing Tool for the USA Region, using the Standard set of statistical variables.
[12]    Jefferson County – Land Parcels. Data available at https://www.jeffco.us/3165/Maps-Data-Download under a Creative Commons Attribution 4.0 International License.
[13]    NASA Socioeconomic Data and Applications Center (SEDAC), Kevin Butler (Esri) – USA Particulate Matter (PM) 2.5 between 1998-2016. Data available at https://services.arcgis.com/jIL9msH9OI208GCb/arcgis/rest/services/USA_PM25_1998_to_2016/FeatureServer 
[14]    OIT - GIS Coordination and Development Program - Statewide Aggregate Parcels in Colorado 2021 (Public) for Arapahoe, Broomfield, Denver, and Douglas Counties. Data available at https://data.colorado.gov/Local-Aggregation/Statewide-Aggregate-Parcels-in-Colorado-2021-Publi/izys-vycy
[15]    OpenStreetMap Contributors – Park Areas, Nature Reserve Areas, Roads, Paths. Data extracted using the HOT OSM Export Tool (https://export.hotosm.org/) with Denver-Aurora-Lakewood CO Metropolitan Statistical Area set as extent definition
[16]    Trust for Public Land - USA 2021 Heat Severity. Data available at https://server6.tplgis.org/arcgis6/services/Heat_Severity_2021/ImageServer
[17]    U.S. Department of Transportation (USDOT) – National Address Database. Data available at https://www.transportation.gov/gis/national-address-database 
[18]    US Census Bureau, Geography Division – American Community Survey 5-Year Estimates (Geodatabase Format, Block Group Level Data for Colorado, 2019). Data available at https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-data.html and documentation at https://www2.census.gov/geo/tiger/TIGER_DP/2019ACS/Metadata/BG_METADATA_2019.txt
[19]    US Census Bureau, Geography Division – Core Based Statistical Areas (Metropolitan/Micropolitan Statistical Area); Counties; County Subdivisions (Colorado); Blocks (2020, Colorado); Block Groups (Colorado); Urban Areas; Places. Data available at https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html and documentation at https://www2.census.gov/geo/pdfs/maps-data/data/tiger/tgrshp2021/TGRSHP2021_TechDoc_Ch4.pdf
[20]    US Department of Transportation - USA Transportation Noise (Road and Aviation, 2018). Data available at https://tiledimageservices.arcgis.com/P3ePLMYs2RVChkJx/arcgis/services/211103a_USA_Transportation_Noise_Road_and_Aviation_2018/ImageServer
[21]    USDA Farm Services Agency – National Agriculture Imagery Program (NAIP): Natural Color. Data available at https://naip.arcgis.com/arcgis/services/NAIP/ImageServer
[22]    USDA Farm Services Agency / ESRI - National Agriculture Imagery Program (NAIP): NDVI Processed. Data available at https://naip.arcgis.com/arcgis/services/NAIP/ImageServer