Shades of Green: A Systematic Review of Uncertainty, Accessibility, and Stakeholder Participation in Models of Green Space and Health

Authors: Kai Ying Lau, Tufts University, Ju Ying Hung, Tufts University, Kyle Monahan*, Tufts University
Topics: Environment, Human-Environment Geography
Keywords: green space, environmental health, geography
Session Type: Poster
Day: 4/4/2019
Start / End Time: 3:05 PM / 4:45 PM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: Download


Modeling of green space and human-environmental systems has increased within recent years. However, evidence for impacts of green space on human health in different settings is unclear. This calls for an interdisciplinary approach to compare working with the research from green space models within urban planning, water resource engineering, environmental health, and other fields. In this systematic literature review, we selected studies that contained quantitative or qualitative models of green space, published between 2007 and 2017. Included models were then classified by their assessment of transportation accessibility, stakeholder participation, equity and environmental justice and statistical uncertainty. Transportation accessibility and stakeholder participation encourage people to partake in usage of green space and active recreation. However, green space related equity and environmental justice issues indicate disparities in distribution of greenery, thus limiting disadvantaged populations access to green space and the health, environmental, and social benefits provided. Therefore, it is important that models of green space are assessed based on their inclusion of these factors, and this may constitute a gap in the field. In total, 766 papers were identified, of which 47 met inclusion criteria. Of those models, only 38% adequately addressed stakeholder participation, 23% addressed transportation accessibility and 61% addressed uncertainty in analysis of green space, which may suggest that there is a need for further development and careful consideration of the metrics and methods employed for green space modeling.

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