Stacking Green Infrastructure Benefits: A Spatial Multi-Criteria Approach to Green Infrastructure Planning in Seattle, Washington
Lau, Kai Ying.
2018
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Abstract: Green infrastructure, defined as any greenery within urban areas, provide a myriad of benefits and services to improve the quality of life for residents. This multi-functionality makes it popular as a sustainable development tool. However, green infrastructure is mainly used or defined as low-impact development technology to mitigate stormwater runoff. Research indicates that there is a ... read morelack of inclusion of multiple green infrastructure benefits in decision-making, and a gap in the analysis of overlapping spatial needs for green infrastructure benefits. This thesis focuses on creating a spatial multi-criteria decision-analysis (S-MCDA) model to determine where green infrastructure will provide multiple ecosystem services. This model determined areas of multi-benefit priority areas for green infrastructure in the City of Seattle. Specifically, this thesis analyzed the spatial, land use and ownership properties of the following ecosystem services: stormwater runoff mitigation, air pollution mitigation, carbon sequestration, urban heat island mitigation, habitat resilience, and access to green space. Social vulnerability was also included in the analysis to investigate any existing social and environmental inequities. Through the S-MCDA analysis the results of this study indicate that the districts with the highest priority need for multiple green infrastructure benefits are: the Southeast, North Seattle, and the industrial and manufacturing areas. Spatial statistics analysis results show there is opportunity and demand for siting green infrastructure based on the need for multiple benefits.
Thesis (M.S.)--Tufts University, 2018.
Submitted to the Dept. of Urban and Environmental Policy and Planning.
Advisor: Barbara Parmenter.
Committee: Sumeeta Srinivasan.
Keywords: Urban planning, Sustainability, and Geographic information science and geodesy.read less - ID:
- d504rx78k
- Component ID:
- tufts:28609
- To Cite:
- TARC Citation Guide EndNote
