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Mapping Green Infrastructure Based on Multifunctional Ecosystem Services: A Sustainable Planning Framework for Utah’s Wasatch Front

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  • Richard leBrasseur

    (Department of Plant, Food and Environmental Sciences, Faculty of Agriculture, Dalhousie University, Truro, NS B3H 4R2, Canada)

Abstract

Most sustainable planning frameworks assess natural and social–economic landscape systems as separate entities, and our understanding of the interrelationships between them is incomplete. Landscape classification in urbanizing environments requires an integrated spatial planning approach to better address the United Nation’s sustainable development challenges. The objective of this research is to apply a multicriteria evaluation which ranked diverse ecosystem–service producing landscapes and synthesize the findings within a unique green infrastructure spatial planning framework. Local government stakeholder derived weighting and GIS classification were operated to map both the urban and natural landscapes of the Salt Lake City region of Utah, one of the most rapidly urbanizing areas in North America. Results were assimilated through five regional landscape typologies—Ecological, Hydrological, Recreational, Working Lands, and Community—and indicated those highest ranked landscape areas which provided multiple ecosystem services. These findings support collaborative decision making among diverse stakeholders with overlapping objectives and illustrates pathways to the development of ecosystem service criteria. This paper contributes to a better understanding of how to integrate data and visualize the strategic approaches required for sustainable planning and management, particularly in urban and urbanizing regions where complex socioecological landscapes predominate.

Suggested Citation

  • Richard leBrasseur, 2022. "Mapping Green Infrastructure Based on Multifunctional Ecosystem Services: A Sustainable Planning Framework for Utah’s Wasatch Front," Sustainability, MDPI, vol. 14(2), pages 1-22, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:2:p:825-:d:723062
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