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Humans are coming to grips with a rapidly changing climate. Impacts that were once thought to be distant prospects are occurring presently. Communities facing difficult choices regarding maintaining access and infrastructure are contemplating novel natural and nature-based features (NNBF): large-scale interventions in the landscape to mitigate hazards and maintain or enhance ecological function. Experts are increasingly relying on landscape visualizations based on scientific models to engage diverse constituencies in the development of adaptation measures such as NNBF. These model-driven perspectival 3D representations of real and recognizable places may be referred to as “data-driven landscape visualizations” (DDLVs). As useful as these tools are, they have fundamental limitations such as being prone to distorting perceptions of uncertainty. This chapter examines evidence within the current literature supporting the application of DDLVs and discusses how the process of their application in sustained, co-creative processes is essential to mitigating their limitations. We present a case study in Charlestown, Rhode Island, USA, where they are being used as tools to address complex climate-related impacts and addressing tradeoffs related to mitigation measures. This case study illustrates how the intensive process of model and visualization development is a site of significant negotiation, engagement, and co-creation, fostering insight among diverse stakeholders. Our findings suggest reframing the ways in which we account for visualization efficacy to better address the role of visualization development as a boundary process.

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