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- 1. Parks as an environmental justice issue: exploring the distribution of recreational resources in Southern CA Phuong Tseng STEER Intern STEER Presentation August 15, 2014
- 2. Introduction Physical inactivity is the 4th leading risk factor for mortality worldwide and is associated with increased risk of cardiovascular disease, diabetes, cancer and depression (WHO, 2014). Parks are important for promoting physical activity and park features such as basketball courts and fields play a role in determining how well parks promote physical activity (Kaczynski et al., 2008). Assessing park features in person is time consuming and research suggests virtual environmental audits using Google Earth may be an efficient alternative to in person audits (Edwards et al., 2013).
- 3. Aims Assess Quality of Parks near Chino, CA Using a Virtual Audit Tool •Assess Park features using Google Earth Determine if Quality of Parks Differs by Socioeconomic Status (SES)
- 4. Background Healthy PLACES is an environmental health study that examines locations where participants are physically active (GPS, accelerometers) Study area ~ 30 miles east of Los Angeles
- 5. Methods Step 1 •Literature: Parks and GIS & remote sensing literature Step 2 •Park audit survey •Park polygons (ESRI Business Analyst) Step 3 •Park quality score •SES & Income tables from Census Bureau
- 6. Preliminary Results Illustration 1: Google Earth’s aerial imagery of a park near Chino, CA Feature(s): Basketball court and picnic tables Illustration 2: Google Earth’s aerial imagery of a park near Chino, CA Feature(s): Tennis court, basketball court, playground, building, parking lot, and walking paths
- 7. Preliminary Results This image shows the park quality scores of 170 parks that were audited in Google Earth. The park quality mean was 46.09%. Median annual household income for parks’ census tracts ranged from 23,362 - 128,313 USD and the mean was 71,865 USD.
- 8. Preliminary Results Park Scores (Mean, 95%CI) for Parks in Census Tracts with Lowest 25% and Highest 25% Median Income. Park Scores (Mean, 95%CI) by Census Tract Income Group
- 9. Preliminary Conclusion The highest 25- percentile income had a significantly higher park quality score (49%) Compared to the lowest 25-percentile income census tracts (43%) (p-value < 0.05) Limitations Missing park polygons from ESRI Business Analyst shape files Park safety, cleanliness and condition are not included in the virtual audit Parks with large tree canopy were difficult to audit
- 10. Future Steps Quality of GIS park polygon shape files (ESRI Business Analysts) will be assessed or corrected (digitized) as needed Additional park features such as park size and park greenness will be assessed and included in the park quality score A subsample of parks will be randomly selected for on-site park audits to compare results with virtual audits Analyses will look at relationship between SES and different park score components
- 12. References Kaczynski AT, Potwarka LR, Saelens BE. Association of park size, distance, and features with physical activity in neighborhood parks. Am J Public Health. 2008;98(8):1451-6. doi: 10.2105/ajph.2007.129064. PubMed PMID: ISI:000257940800021. Edwards N, Hooper P, Trapp GSA, Bull F, Boruff B, Giles-Corti B. Development of a Public Open Space Desktop Auditing Tool (POSDAT): A remote sensing approach. Applied Geography. 2013;38(0):22-30. doi: http://dx.doi.org/10.1016/j.apgeog.2012.11.010.
- 13. Thank you! Funders: National Institute of Environmental Health Sciences (NIEHS), National Institute of Health, Center for Occupational and Environmental Health, School of Public Health, STEER Program Supporters: Estela Almanza; Michael Jerrett; Michael Bates, Director of STEER Program; Sadie Costello, Associate Director of STEER Program; Gayle Cepparo, Project Coordinator; Shizuka Kuroiwa, Web and Graphic Designer
Editor's Notes
- Hello Everyone! Thank you for being here today. My name is Phuong Tseng and I am a 2014 Summer STEER Intern working in the Geographic Information Science Lab this summer. Through this internship, I learned of the importance of parks and the benefits that parks provide to community members. Thus, I’m here to present this presentation, “Parks as an environmental justice issue: exploring the distribution of recreational resources in Southern California.” My presentation is going to focus on the environmental justice aspect of park quality. Research suggests that lower income communities have parks of lower quality so for our project we set out to examine whether we could find evidence of this injustice in a group of parks in southern California. To do this we evaluated park features of 170 parks by means of a virtual audit and in just a minute I’ll explain what this is all about. But first of all, a little bit of background on why this is important…..
- According to World Health Organization, “Physical inactivity is the 4th leading risk factor for mortality worldwide and is associated with increased risk of cardiovascular disease, diabetes, cancer and depression.” And Kaczynski suggests that “parks are important for promoting physical activity” since recreational resources or features such as basketball courts, playgrounds, and fields play a role in determining how well parks promote physical activity Therefore, we assessed park features using Google Earth since research suggests that virtual environmental audits are more efficient and economical than on-site in person audits
- To assess park features, this study used Google Earth to conduct virtual park audits within approximately 30 miles of Chino, CA and used the audit results to calculate an overall park quality score for each park as well as geo-visualize the park quality score together with census tracts’ socioeconomic status (SES) data of the parks to spatially examine whether there is a relationship between park quality and SES.
- The reason why we looked at parks near Chino, CA is because there is an environmental health study that is looking at physical activity patterns of participants near Chino, CA using GPS and accelerometers. This study area is about 30 miles east of LA.
- And here are the methods that we used to approach this project. Step 1: We looked into parks, GIS, and remote sensing literature to gain more understanding of how to conduct virtual park audits. Step 2: We obtained a park audit survey from a virtual audit tool developed and validated by researchers in Australia. Then, we used ArcGIS to export park polygons (ESRI Business Analyst) and visualize these park polygons in Google Earth for virtual park auditing to assess physical activity and recreational features such as basketball courts, fields, playgrounds, trees, water features, and more. Parks with more features received higher park quality scores. We obtained annual median household income for parks’ census tracts from US Census Bureau (Average over years 2008-2012) to visually explore whether parks’ quality scores were associated with parks’ census tract SES (household income). Here is a cartoon picture that I’ll use to help you all understand how I conducted these park audits. For example: this park has many features such as a pond, swings or playground, bicycle and walking paths. To assess park activity, this study conducted park audits within 5 kilometers of participants’ homes
- Preliminary Results: These two images are Google Earth’s aerial imagery of parks near Chino, CA Other: We were unable to complete park audits; thus, we are missing park polygons from ESRI Business Analysts shape files. Park safety, cleanliness and the condition of park features are not included in the virtual audit and parks with large tree canopy were difficult to audit; hence, we could not appropriately visualize and analyze our results. Parks that were located within census tracts with the highest 25-percentile income had a significantly higher park quality score (49%) compared to parks located within the lowest 25-percentile income census tracts (43%) (p-value < 0.05). Although the difference in park score was small these results suggest that this disparity should be examined further.
- MORE NOTES ON WHAT TO SAY VERBALLY FOR SLIDE SHOWING BAR GRAPH: So, the map did not show a clear pattern of an overall relationship between census tract income level and park quality, BUT, when we compared the lowest 25-percentile income group to the highest 25-percentile income group we found that park scores were significantly higher for the highest income group: the highest income group had a mean park score of 48.6 while the lowest income group had a mean park score of 42.7.
- • Quality of GIS park polygon shapefiles (ESRI Business Analysts) will be assessed or corrected (digitized) as needed • Additional park features such as park size and park greenness will be assessed and included in the park quality score • A subsample of parks will be randomly selected for on-site park audits to compare results with virtual audits • Analyses will look at relationship between SES and different park score components
- 1. Kaczynski AT, Potwarka LR, Saelens BE. Association of park size, distance, and features with physical activity in neighborhood parks. Am J Public Health. 2008;98(8):1451-6. doi: 10.2105/ajph.2007.129064. PubMed PMID: ISI:000257940800021. 2. Edwards N, Hooper P, Trapp GSA, Bull F, Boruff B, Giles-Corti B. Development of a Public Open Space Desktop Auditing Tool (POSDAT): A remote sensing approach. Applied Geography. 2013;38(0):22-30. doi: http://dx.doi.org/10.1016/j.apgeog.2012.11.010.