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Evaluating street view exposure measures of visible green space for health research

Abstract

Urban green space, or natural environments, are associated with multiple physical and mental health outcomes. Several proposed pathways of action for these benefits (e.g., stress reduction and attention restoration) require visual perception of green space; however, existing green space exposure measures commonly used in epidemiological studies do not capture street-scale exposures. We downloaded 254 Google Street View (GSV) panorama images from Portland, Oregon and calculated percent of green in each image, called Green View Index (GVI). For these locations we also calculated satellite-based normalized difference vegetation index (NDVI), % tree cover, % green space, % street tree buffering, distance to parks, and several neighborhood socio-economic variables. Correlations between the GVI and other green space measures were low (−0.02 to 0.50), suggesting GSV-based measures captured unique information about green space exposures. We further developed a GVI:NDVI ratio, which was associated with the amount of vertical green space in an image. The GVI and GVI:NDVI ratio were weakly related to neighborhood socioeconomic status and are therefore less susceptible to confounding in health studies compared to other green space measures. GSV measures captured unique characteristics of the green space environment and offer a new approach to examine green space and health associations in epidemiological research.

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References

  1. Shanahan DF, Bush R, Gaston KJ, Lin BB, Dean J, Barber E, et al. Health benefits from nature experiences depend on dose. Sci Rep. 2016 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4917833/

  2. Astell-Burt T, Feng X, Kolt GS. Is neighborhood green space associated with a lower risk of type 2 diabetes? Evidence from 267,072 Australians. Diabetes Care. 2014;37:197–201.

    Article  Google Scholar 

  3. Ebisu K, Holford TR, Bell ML. Association between greenness, urbanicity, and birth weight. Sci Total Environ. 2016;542:750–6.

    Article  CAS  Google Scholar 

  4. Beyer KM, Kaltenbach A, Szabo A, Bogar S, Nieto FJ, Malecki KM. Exposure to neighborhood green space and mental health: evidence from the survey of the health of Wisconsin. Int J Environ Res Public Health. 2014;11:3453–72.

    Article  Google Scholar 

  5. Bratman GN, Hamilton JP, Daily GC. The impacts of nature experience on human cognitive function and mental health. Ann N Y Acad Sci. 2012;1249:118–36.

    Article  Google Scholar 

  6. Takano T, Nakamura K, Watanabe M. Urban residential environments and senior citizens’ longevity in megacity areas: the importance of walkable green spaces. J Epidemiol Community Health. 2002;56:913–8.

    Article  CAS  Google Scholar 

  7. Baró F, Chaparro L, Gómez-Baggethun E, Langemeyer J, Nowak DJ, Terradas J. Contribution of ecosystem services to air quality and climate change mitigation policies: the case of urban forests in Barcelona, Spain. Ambio. 2014;43:466–79.

    Article  Google Scholar 

  8. Maimaitiyiming M, Ghulam A, Tiyip T, Pla F, Latorre-Carmona P, Halik Ü, et al. Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation. ISPRS J Photogramm. Remote Sens. 2014;89:59–66.

    Google Scholar 

  9. Lottrup L, Grahn P, Stigsdotter UK. Workplace greenery and perceived level of stress: Benefits of access to a green outdoor environment at the workplace. Landsc Urban Plan. 2013;110:5–11.

    Article  Google Scholar 

  10. Coombes E, Jones AP, Hillsdon M. The relationship of physical activity and overweight to objectively measured green space accessibility and use. Soc Sci Med. 2010;70:816–22.

    Article  Google Scholar 

  11. Wendel HEW, Zarger RK, Mihelcic JR. Accessibility and usability: Green space preferences, perceptions, and barriers in a rapidly urbanizing city in Latin America. Landsc Urban Plan. 2012;107:272–82.

    Article  Google Scholar 

  12. Lovasi GS, Schwartz-Soicher O, Quinn JW, Berger DK, Neckerman KM, Jaslow R, et al. Neighborhood safety and green space as predictors of obesity among preschool children from low-income families in New York City. Prev Med. 2013;57:189–93.

    Article  Google Scholar 

  13. Laumann K, Gärling T, Stormark KM. Selective attention and heart rate responses to natural and urban environments. J Environ Psychol. 2003;23:125–34.

    Article  Google Scholar 

  14. Ulrich RS. Natural versus urban scenes: Some psychophysiological effects. Environ Behav. 1981;13:523–56.

    Article  Google Scholar 

  15. Groenewegen PP, Berg AE, van den, Vries S, de, Verheij RA. Vitamin G: effects of green space on health, well-being, and social safety. BMC Public Health. 2006;6:149.

    Article  Google Scholar 

  16. Li X, Zhang C, Zhang C, Li W, Ricard R, Meng Q, Zhang W. Assessing street-level urban greenery using Google Street View and a modified green view index. Urban Urban. 2015;14:675–85.

    Article  Google Scholar 

  17. Li X, Zhang C, Li W, Kuzovkina YA, Weiner D. Who lives in greener neighborhoods? The distribution of street greenery and its association with residents’ socioeconomic conditions in Hartford, Connecticut, USA. Urban Urban. 2015;14:751–9.

    Article  Google Scholar 

  18. van Rossum G, Drake Jr FL. Extending and embedding Python, Release 2.7. Python Softw Found Wolfeboro Falls. 2010

  19. Bradski G, et al. The opencv library. Dr Dobbs J. 2000;25:120–6.

    Google Scholar 

  20. Moore RT, Hansen MC. Google Earth Engine: a new cloud-computing platform for global-scale earth observation data and analysis. In: AGU Fall Meeting Abstracts; 2011. p. 02. http://adsabs.harvard.edu/abs/2011AGUFMIN43C..02M

  21. Zhu Z, Wang S, Woodcock CE. Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images. Remote Sens Environ. 2015;159:269–77.

    Article  Google Scholar 

  22. ArcGIS E. 10.3. 1; Environmental Systems Research Institute, Inc. Redlands; 2015

  23. Studio R. RStudio: integrated development environment for R. RStudio Inc. Boston, Massachusetts; 2012

  24. Cusack L, Larkin A, Carozza S, Hystad P. Associations between residential greenness and birth outcomes across texas. Environ Res. 2017;152:88–95.

    Article  CAS  Google Scholar 

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Acknowledgements

The authors would like to thank Google for developing and maintaining the Google Street View and Google Earth Engine datasets and APIs. The authors would also like to thank Leanne Cusack for her thoughts and contributions while developing presentation materials.

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Correspondence to Andrew Larkin.

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Larkin, A., Hystad, P. Evaluating street view exposure measures of visible green space for health research. J Expo Sci Environ Epidemiol 29, 447–456 (2019). https://doi.org/10.1038/s41370-018-0017-1

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