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

Schaefer, Mathias; Thinh, Nguyen Xuan; Greiving, Stefan

doi:10.3390/su12020635

Cited by 20 publications

(7 citation statements)

References 65 publications

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“…In particular, large public open green spaces are more located throughout the southern districts of the city. In addition to an uneven distribution of green areas, an initial GIS-based Multi Criteria Fuzzy Analysis by Schaefer et al (2020) revealed that health-related environmental burdens such as heat stress and noise pollution are clustered on different spatial scales across the entire city, with the Dortmund Marten subdistrict as one hotspot. ).…”

Section: Case Study Area and Previous Workmentioning

confidence: 99%

“…For equity reasons, another precondition was that GI interventions need to be accessible within walking distance and publicly available for citizens in Dortmund Marten. With subject-specific knowledge of the specialists and GIS-based indicator maps of Schaefer et al (2020), the first measures were outlined and mapped by both working groups to identify possible hotspots for action. The role of science was to provide information on current analysis results, while the practice participants contributed tangible measures in this area.…”

Section: 'Green Marten' Cooperative Workhopmentioning

confidence: 99%

“…Regarding socio-ecological inequalities in the long run, environmental factors and demographic data should be monitored via indicators to quantify advantages and disadvantages to the local population after GI implementation. The Urban Climate Resilience Index (UCRI) proposed by Schaefer et al (2020) would serve as a suitable example. The Meilenstein office in Dortmund Marten should be consolidated as a fixed infrastructure, evolving into a persistent living to collect profound feedback on the analysis results while also giving attention continuous optimization in response to citizen and stakeholder interaction.…”

Section: Socio-ecological Challengesmentioning

confidence: 99%

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Between vision and action: the predicted effects of co-designed green infrastructure solutions on environmental burdens

Schaefer

2022

Urban Ecosyst

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Green Infrastructure (GI) is gaining wide recognition in cooperative research projects seeking to find solutions for climate adaptation in urbanized areas. However, the potential effects of co-produced GI plans and the underlying preparation process are rarely evaluated. To bridge this gap, the aim of this article is to examine what works in addressing environmental burdens in the urban neighborhood of Dortmund Marten, Germany. As part of a larger transdisciplinary process, selective GI measures were delineated in the case study area through a cooperative workshop between scientists and urban planners. Workshop ideas were incorporated into a mitigative scenario considering a hot summer day to quantify the effects of the derived GI measures on thermal comfort and particulate matter dispersion (PM10 and PM2.5). To evaluate the experiences of the science-practice collaboration, the viewpoints of researchers and urban planners on learning effects, knowledge integration, and GI planning were summarized and compared via an online survey. The results indicate that the proposed GI measures could reduce physiological equivalent temperature (PET) by 25 °C. At the same time, additional roadside trees could increase PM10 concentrations by up to 36 µg/m3 due to wind blocking effects. Reflections on the science-practice workshop show that learning effects were higher for the participating researchers than for planning practitioners, while the integration of individual expertise during the workshop was more difficult for academics. These findings point to the importance of continuous reflections on individual understandings in cooperating stakeholder groups and the value of the evaluation of outcomes in transdisciplinary GI planning.

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Section: Case Study Area and Previous Workmentioning

confidence: 99%

Section: 'Green Marten' Cooperative Workhopmentioning

confidence: 99%

Section: Socio-ecological Challengesmentioning

confidence: 99%

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Between vision and action: the predicted effects of co-designed green infrastructure solutions on environmental burdens

Schaefer

2022

Urban Ecosyst

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“…A fuzzy hybrid model in a GIS framework is proposed in Schaefer et al (2020) to evaluate the climate resilience in metropolitan cities. In Cardone and Di Martino (2021) the authors implement a hierarchical fuzzy multicriteria decision model in a GIS platform to find the optimal localization of school buildings in urban areas.…”

Section: Related Workmentioning

confidence: 99%

A GIS-based framework using fuzzy relation equation system solutions in urban planning

Cardone

Martino

2022

J Ambient Intell Human Comput

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Several fuzzy decision models are proposed in literature to solve urban planning problems. In this research we present a novel GIS-based framework to solve decision problems in urban planning based on a System of Fuzzy Relation Equations in which the unknowns represent characteristics affecting observable facts constituting the input variables. Aim of this research is to partition the urban study area into subzones, each of which identifies a sub-area of the study area within which the set of analyzed characteristics are homogeneous. The study area is initially decomposed in atomic urban areas called microzones; for each microzone are calculated the greatest and lowest solutions of a System of Fuzzy Relation Equations by using the Universal solution Algorithm and are calculated and fuzzified the values of the output variables. Spatially adjoining microzones with same output variables are dissolved forming homogeneous urban areas with reference to the problem analyzed, called Urban Contexts. For each output variable a thematic map is constructed; in addition, a thematic map of its reliability is created. This framework is tested on a study area given by the district of Ponticelli in the municipality of Naples (Italy); comparison tests performed with respect to a previous GIS-based framework based on a System of Fuzzy Relation Equations show that our method provides a more detailed knowledge of the characteristics of the urban study area with reference to the problem dealt with.

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“…When it comes to vulnerability or resilience assessment, geographic information systems (GIS) have become powerful tools for identifying vulnerable communities and locations, at different scales [37][38][39]. There are also many studies that have conceived different GIS methods to predict, evaluate, and analyze the vulnerability and resilience of social environmental systems [40][41][42][43][44]. GIS can help governments, environmental agencies, and insurance companies to improve prevention, early warning mechanisms, and mitigation efforts using predictive analytics.…”

Section: Introductionmentioning

confidence: 99%

Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China

Xiang

Proverbs

2020

Water

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While various measures of mitigation and adaptation to climate change have been taken in recent years, many have gradually reached a consensus that building community resilience is of great significance when responding to climate change, especially urban flooding. There has been a dearth of research on community resilience to urban floods, especially among transient communities, and therefore there is a need to conduct further empirical studies to improve our understanding, and to identify appropriate interventions. Thus, this work combines two existing resilience assessment frameworks to address these issues in three different types of transient community, namely an urban village, commercial housing, and apartments, all located in Wuhan, China. An analytic hierarchy process–back propagation neural network (AHP-BP) model was developed to estimate the community resilience within these three transient communities. The effects of changes in the prioritization of key resilience indicators under different environmental, economic, and social factors was analyzed across the three communities. The results demonstrate that the ranking of the indicators reflects the connection between disaster resilience and the evaluation units of diverse transient communities. These aspects show the differences in the disaster resilience of different types of transient communities. The proposed method can help decision makers in identifying the areas that are lagging behind, and those that need to be prioritized when allocating limited and/or stretched resources.

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

Cited by 20 publications

References 65 publications

Between vision and action: the predicted effects of co-designed green infrastructure solutions on environmental burdens

Between vision and action: the predicted effects of co-designed green infrastructure solutions on environmental burdens

A GIS-based framework using fuzzy relation equation system solutions in urban planning

Assessing Community Resilience to Urban Flooding in Multiple Types of the Transient Population in China

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