Journal
URBAN FORESTRY & URBAN GREENING
Volume 40, Issue -, Pages 236-244Publisher
ELSEVIER GMBH
DOI: 10.1016/j.ufug.2018.02.007
Keywords
Curve estimation; Dose responses; Eye-level vegetation density; Green stormwater infrastructure; Preference
Categories
Funding
- NSF [1261582]
- Project Title: CIF21 DIBBs: Brown Dog
- National Center of Supercomputing Applications
- Office of Advanced Cyberinfrastructure (OAC)
- Direct For Computer & Info Scie & Enginr [1261582] Funding Source: National Science Foundation
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Green Infrastructure (GI) refers to the natural spaces in a city that improve urban ecology and bring social, economic, and environmental benefits to residents and communities. Although we know a good deal about people's preference for urban forests, we know little about how people reaction to other types of GI and even less about how varying levels of vegetation density influence preference. Without this knowledge, planners and designers risk creating landscapes that people experience as insufficiently restorative. To understand people's preference for different types and vegetation density levels of GI, we conducted three GI preference surveys and utilized a new technology called Brown Dog's Green Index Extractor to calculate vegetation density. We found that, overall, tree density and understory vegetation density are positively associated with preference in a power-curve relationship. The nature of the relationship between bioretention density and preference remains unclear, even though it is significant and positive. The findings presented here expand our knowledge of landscape preference to the emerging field of GI. Designers and planners can use these results to create preferred landscapes that manage stormwater that also promote human well-being. Future studies might explore the relationship between GI density and preference further by investigating other aspects of GI such as planting designs and maintenance and the relationships between GI's vegetation density and various health and well-being indicators.
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