How Can Climate Resilience Be Measured and Visualized? Assessing a Vague Concept Using GIS-Based Fuzzy Logic

Mathias Schaefer, Nguyen Xuan Thinh and Stefan Greiving
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Mathias Schaefer: Department of Spatial Information Management and Modelling (RIM), TU Dortmund University, 44227 Dortmund, Germany
Nguyen Xuan Thinh: Department of Spatial Information Management and Modelling (RIM), TU Dortmund University, 44227 Dortmund, Germany
Stefan Greiving: Institute of Spatial Planning (IRPUD), TU Dortmund University, 44227 Dortmund, Germany

Sustainability, 2020, vol. 12, issue 2, 1-30

Abstract: As negative impacts of climate change tend to increase in the future, densely-populated cities especially need to take action on being robust against natural hazards. Consequently, there is a growing interest from scientists in measuring the climate resilience of cities and regions. However, current measurements are usually assessed on administrative levels, not covering potential hotspots of hazardous or sensitive areas. The main aim of this paper focusses on the measurement of climate resilience in the City of Dortmund, Germany, using Geographic Information Systems (GIS). Based on a literature review, we identified five essential components of climate resilience and initially designed a theoretical framework of 18 indicators. Since climate resilience is still a vague concept in scientific discourses, we implemented local expert knowledge and fuzzy logic modelling into our analysis. The benefit of this study not only lies in the fine-scale application, but also in the relevance for multiple disciplines by integrating social and ecological factors. We conclude that climate resilience varies within the city pattern, with the urban core tending to be less resilient than its surrounding districts. As almost the entire geodata set used is freely available, the presented indicators and methods are to a certain degree applicable to comparable cities.

Keywords: climate resilience; sustainable development; urban planning; remote sensing; fuzzy logic; compromise programming (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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