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  • 标题:Images to Evoke Decision-Making: Building Compelling Representations for Stakeholder-Driven Futures
  • 本地全文:下载
  • 作者:Daniel Cronan ; E. Jamie Trammell ; Andrew (Anaru) Kliskey
  • 期刊名称:Sustainability
  • 印刷版ISSN:2071-1050
  • 出版年度:2022
  • 卷号:14
  • 期号:5
  • 页码:2980
  • DOI:10.3390/su14052980
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:Contemporary landscape planning challenges require an increasingly diverse ensemble of voices, including regional stakeholders, physical scientists, social scientists, and technical experts, to provide insight into a landscape’s past trends, current uses, and desired future. To impactfully integrate these disparate components, stakeholder-driven research must include clear lines of communication, share data transparently, and slowly develop trust. Alternative future scenario representations aim to generate conversations through discourse, evoke scenario-based stakeholder input, and ensure stakeholder-based revisions to research models. The current literature lacks a metric for gauging effectiveness and a framework for optimal evaluation for future scenario representations. We have developed and applied a metric for a ranked set of compelling scenario representations using stakeholder input from an active research project. Researchers surveyed stakeholders through a case study in Idaho’s Magic Valley to gauge the effectiveness of each representational approach. To improve future stakeholder-driven geodesign projects and gaps in the research literature, this project provides a ranking of graphic strategies based on the stakeholder survey. Additionally, we provide examples and evaluate graphic representation strategies that can stimulate meaningful conversations, create common understandings, and translate research processes and findings to a variety of audiences. The results of this study intend to provide landscape architects, landscape planners, and geodesign specialists with a framework for evaluating compelling future scenario representations for a stakeholder group.
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