Assessing urban adaptive capacity to climate change

Araya-Muñoz, Dahyann; Metzger, Marc J.; Stuart, Neil; Wilson, Anne M.; Álvarez, Luis

doi:10.1016/j.jenvman.2016.08.060

Cited by 31 publications

(15 citation statements)

References 36 publications

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“…Level of education is often used as a proxy degree of preparedness for dealing with shocks and reinforces responses [3,15,25,85,86]. Higher education levels have been considered as elements of adaptive capacity that can affect the productivity yields in R&D and innovation sectors [87–91].…”

Section: Methodsmentioning

confidence: 99%

Constructing a comprehensive disaster resilience index: The case of Italy

et al. 2019

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Measuring disaster resilience is a key component of successful disaster risk management and climate change adaptation. Quantitative, indicator-based assessments are typically applied to evaluate resilience by combining various indicators of performance into a single composite index. Building upon extensive research on social vulnerability and coping/adaptive capacity, we first develop an original, comprehensive disaster resilience index (CDRI) at municipal level across Italy, to support the implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030. As next, we perform extensive sensitivity and robustness analysis to assess how various methodological choices, especially the normalisation and aggregation methods applied, influence the ensuing rankings. The results show patterns of social vulnerability and resilience with sizeable variability across the northern and southern regions. We propose several statistical methods to allow decision makers to explore the territorial, social and economic disparities, and choose aggregation methods best suitable for the various policy purposes. These methods are based on linear and non-liner normalization approaches combining the OWA and LSP aggregators. Robust resilience rankings are determined by relative dominance across multiple methods. The dominance measures can be used as a decision-making benchmark for climate change adaptation and disaster risk management strategies and plans.

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Section: Methodsmentioning

confidence: 99%

Constructing a comprehensive disaster resilience index: The case of Italy

et al. 2019

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“…The use of a fuzzy gamma overlay allows an exploration of the relationships between the multiple input criteria and was chosen in order to minimize the omitted information coming from the overlay, which is based on the sum or product algorithm [44]. The gamma factor range is within 0-1, where for gamma values between 0.6 and 0.8, the resulting determinant aggregation falls within the entry criteria values [45]. Therefore, for the purpose of our study, the utilized gamma value was 0.8.…”

Section: Impact Of Heatwavesmentioning

confidence: 99%

“…The study used a fuzzy gamma overlay approach (for more details, see [45,54]) to spatially analyze potential heatwave impacts in the three cities. In order to analyze differences between the three cities (Prague, Brno, Pilsen), the "inter-city" scale comparison was used.…”

Section: Spatial Assessmentmentioning

confidence: 99%

Participatory Climate Change Impact Assessment in Three Czech Cities: The Case of Heatwaves

et al. 2018

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Abstract:Cities are complex socioecological systems that are particularly vulnerable to the impacts of climate change and are also exposed to other trends, such as urbanization and population aging. Due to the changing climate, days with extreme temperatures are expected to become more numerous, which is particularly important for urban areas, where the urban heat island phenomenon is observed. This study presents an example of a spatially explicit potential climate change impact assessment of heatwaves integrating both science and stakeholder participation for three large Czech cities (Prague, Brno, and Pilsen). Stakeholder participation exercises were used to prioritize climate change risks, provide impetus and opportunity for knowledge co-production, and support adaptation planning. Potential climate change impacts of heatwaves in the three Czech cities for the current baseline and for the future (2021-2040) using Representative Concentration Pathways (RCPs)-RCP 4.5 and RCP 8.5, were mapped at two levels describing "in-city" and "inter-city" comparison. When comparing the potential impact of heatwaves across the three cities ("inter-city"), the most affected city is Brno, with 10.5% of its area in the very high impact category for the baseline and both RCPs. The "in-city" comparison shows the differences between the baseline and future scenarios of each city. The assessment of heatwaves' impacts was further used to support urban adaptation planning.

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“…al., 2016). However, the factors that determine the adaptability of urban households are poorly understood (Nhuan et al, 2016;Toole et al, 2016) and most studies that attempt to quantify adaptive capacity are performed at spatial scales larger than households (Adger and Vincent, 2005;Araya-Muñoz et al, 2016) and in rural locations (Wall and Marzall, 2006;Below et al, 2012;Lockwood et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Developing an Instrument to Measure Autonomous Adaptive Capacity to Climate Change among Urban Households

et al. 2018

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The capacity of households in urban environments to adapt and react to climate change can affect the resilience of the whole community, and instruments for systematically measuring that capacity are needed. We used Raleigh, NC as a case study to explore the dimensions of autonomous adaptive capacity of urban households and to create a scale and associated survey instrument to measure them. Our approach was guided by four capitals that support human livelihoods: social, human, physical, and financial. We surveyed 200 households in Raleigh, NC, and used a principal components analysis to test the scale and survey instrument. Results suggest the scale is a useful and concise tool. Three major dimensions were present among the scale items: financial capital, political awareness, and access to resources. Together, these three dimensions can be used to measure adaptive capacity among different households. These findings are supported by similar work illustrating the value of income inequality and political awareness as indicators of adaptive capacity. Our results also demonstrate that complex relationships among the livelihood capitals may confound our ability to measure financial, physical, and human capitals separately. This framework for assessing adaptive capacity of households, with further refinement and testing, may be used in urban areas to evaluate programs designed to impact resilience to climate change.

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Assessing urban adaptive capacity to climate change

Cited by 31 publications

References 36 publications

Constructing a comprehensive disaster resilience index: The case of Italy

Constructing a comprehensive disaster resilience index: The case of Italy

Participatory Climate Change Impact Assessment in Three Czech Cities: The Case of Heatwaves

Developing an Instrument to Measure Autonomous Adaptive Capacity to Climate Change among Urban Households

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