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Landscape Design toward Urban Resilience: Bridging Science and Physical Design Coupling Sociohydrological Modeling and Design Processopen access

Authors
Kwak, YoonshinDeal, BrianMosey, Grant
Issue Date
May-2021
Publisher
MDPI
Keywords
landscape architecture; urban resilience; Geodesign; Planning Support Systems (PSSs); evidence-based design; design application
Citation
SUSTAINABILITY, v.13, no.9
Journal Title
SUSTAINABILITY
Volume
13
Number
9
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/87321
DOI
10.3390/su13094666
ISSN
2071-1050
2071-1050
Abstract
Given that evolving urban systems require ever more sophisticated and creative solutions to deal with uncertainty, designing for resilience in contemporary landscape architecture represents a cross-disciplinary endeavor. While there is a breadth of research on landscape resilience within the academy, the findings of this research are seldom making their way into physical practice. There are existent gaps between the objective, scientific method of scientists and the more intuitive qualitative language of designers and practitioners. The purpose of this paper is to help bridge these gaps and ultimately support an endemic process for more resilient landscape design creation. This paper proposes a framework that integrates analytic research (i.e., modeling and examination) and design creation (i.e., place-making) using processes that incorporate feedback to help adaptively achieve resilient design solutions. Concepts of Geodesign and Planning Support Systems (PSSs) are adapted as part of the framework to emphasize the importance of modeling, assessment, and quantification as part of processes for generating information useful to designers. This paper tests the suggested framework by conducting a pilot study using a coupled sociohydrological model. The relationships between runoff and associated design factors are examined. Questions on how analytic outcomes can be translated into information for landscape design are addressed along with some ideas on how key variables in the model can be translated into useful design information. The framework and pilot study support the notion that the creation of resilient communities would be greatly enhanced by having a navigable bridge between science and practice.
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