Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58164
Title: Does density of green infrastructure predict preference?
Authors: Pongsakorn Suppakittpaisarn
Bin Jiang
Marcus Slavenas
William C. Sullivan
Keywords: Agricultural and Biological Sciences
Environmental Science
Issue Date: 1-Jan-2018
Abstract: © 2018 Elsevier GmbH. 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.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85042864535&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/58164
ISSN: 16108167
16188667
Appears in Collections:CMUL: Journal Articles

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