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The overall objective of this study is envisaged to provide decision makers with actionable insights and access to multi-risk maps for the most in-danger stave churches (SCs) among the existing 28 churches at high spatial resolution to better understand, reduce and mitigate single- and multi-risk. In addition, the present contribution aims to provide decision makers with some information to face the exacerbation of the risk caused by the expected climate change.

Material and data collection started with the consultation of the available literature related to: (1) SCs' conservation status, (2) available methodologies suitable in multi-hazard approach and (3) vulnerability leading indicators to consider when dealing with the impact of natural hazards specifically on immovable cultural heritage.

The paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. The results highlight the danger at which the SCs of Røldal, in case of floods, and of Ringebu, Torpo and Øye, in case of landslide, may face and stress the urgency of increasing awareness and preparedness on these potential hazards.

The contribution for the first time aims to homogeneously collect and report all together existing spread information on architectural features, conservation status and geographical attributes for the whole group of SCs by accompanying this information with as much as possible complete 2D sections collection from existing drawings and novel 3D drawn sketches created for this contribution. Then the paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. Then it highlights the danger of floods and landslides at which the 28 SCs are subjected. Finally it reports how these risks will change under the ongoing impact of climate change.

This paper aims to clarify the resistance degree of group road logistics to flood disaster resilience. The paper measures the resilience of group road logistics by establishing network structure model. The purpose of this study is to improve the resilience of road log.

This paper adopts Delphi method to collect data, interviews mainly flood management experts and supply chain risk management experts, and then analyzes the data through the network structure model combined with interpretative structure model (ISM) and analytical network process (ANP).

The results show that flood frequency and drainage systems are the main factors affecting the resilience of road transport logistics in urban areas. These research results provide useful guidance for the effective planning and design of urban road construction and infrastructure.

However, the main factors affecting the resilience of road transport logistics are likely to change with the development of factors such as climate, economy and environment. Therefore, in future work, the authors' research will focus on the further application of this evaluation method.

The results show that the impact of flooding on the four dimensions of road logistics resilience varies. This shows that in deciding what intervention measures are to be taken to improve the resilience of the road network to flooding, various measures need to be considered.

This paper provides a more scientific analysis of the risk management ability of the road network in the face of floods. In addition, it also provides a useful reference for urban road planners.

This paper addresses a clear need to study how to build models to improve the resilience of road logistics in flood risk.

Information on the impact of flooding is fundamental to mitigating flood risk in residential property. This paper aims to provide insight into the seller disclosure of flood risk and buyer behaviour in the absence of mandated seller disclosure.

This paper adopts a case study approach to critically evaluate the matrix of flood information available for buyers purchasing residential property in Brisbane, Queensland. This paper uses big data analytic techniques to extract and analyse internet data from online seller agents and buyer platforms to gain an understanding of buyer awareness and consideration of flood risk in the residential property market.

Analysis of property marketing data demonstrates that seller agents voluntarily disclose flood impact only in periods where a flooding event is anticipated and is limited to asserting a property is free of flood risk. Analysis of buyer commentary demonstrates that buyers are either unaware of flood information or are discounting the risk of flood in favour of other property and locational attributes when selecting residential property.

This research suggests that improved and accessible government-provided flood mapping tools are not enhancing buyers’ understanding and awareness of flood risk. Accordingly, it is recommended that mandatory disclosure be introduced in Queensland so that buyers are more able to manage risk and investment decisions before the purchase of residential property.

This paper contributes to existing literature on raising community awareness and understanding of natural disaster risks and makes a further contribution in identifying mandatory disclosure as a mechanism to highlight the risk of flooding and inform residential property purchasers.

The survivorship of firms under extreme weather poses an essential question about the local economy's health. Over 90% of agricultural banks are categorized as community banks, which are important financial institutions promoting local growth. While previous studies suggest that climate change and weather shocks adversely impact community banks' resiliency, studies on whether these institutions engage in risk-reducing management strategies have been limited. In this study, the authors examine strategic choices of local community banks when facing flood events which include (1) safety net increase, (2) portfolio diversification, and (3) branch opening. These strategic choices are the coping mechanisms banks can take to survive while affecting the local competitive lending market.

The authors use panel-fixed effect regressions based on the storm data from National Oceanic and Atmospheric Administration (NOAA)'s National Weather Service (NWS) and the call reports from the Federal Deposit Insurance Corporation (FDIC). The authors focus on community banks' account variable characteristics and the number of offices to examine whether community banks take an active role in managing flood risk.

Results suggest that community banks do employ the selected strategic choices to a certain degree, as it is found that there is an increase in the core capital that absorbs shocks and portfolio diversification. However, the magnitudes of these activities are rather small and not large enough to fully mitigate the climate risk. Also, the authors do not find any evidence of branch expansion associated with local floods.

This study contributes to the literature by examining different strategic choices of community banks in the face of natural uncertainty. Even though concerns of climate risk have been raised in the regulatory setting, a lack of guidance or assessment tools could contribute to the passive action of these community banks, even though climate risks can have a significant economic impact. Thus, the evidence documented from this study calls for further guidelines and the importance of highlighting climate risks on community banks so that they can actively engage in risk-reducing strategies.

The purpose of this study is to explore multiple stakeholders managing the different type of knowledge in a flood-prone area. Different stakeholders hold different types of knowledge in their area of interest, and both knowledge streams have their intrinsic potentials and limitations. In this paper, the issue of knowledge complementarity is explored in the context of flood hazards. Hazards such as floods may appear messy, unpredictable, with unsorted and unorganised forms of data, information and knowledge on the part of diverse stakeholders.

Case study design had been used in this study to explore how stakeholders: Orang Asli, Malay, and humanitarian organisations manage the differences in terms of type of knowledge each of them have. To illicit the response from participants from each of the stakeholders, in-depth interviews had been used.

This research has led to the development of a conceptual framework based on the case study. The lessons learned from the framework is discussed, together with the barriers to their implementation.

This paper presents a research case study on multiple stakeholders in the district of Pekan, the state of Pahang, Malaysia, and how these multiple stakeholders manage flood hazards with their different types of knowledge.

This study aims to review the features and challenges of the flood relief chain, identifies administrative measures during and after the flood occurrence and prioritizes them using two machine learning (ML) and analytic hierarchy process (AHP) methods. This paper aims to provide a prioritization program based on flood conditions that optimize flood management and improves society’s resilience against flood occurrence.

The collected database in this paper has been trained by using ML algorithms, including support vector machine (SVM), Naive Bayes (NB) and k-nearest neighbors (kNN), to create a prioritization program. Furthermore, the administrative measures in two phases of during and after the flood are prioritized by using the AHP method and questionnaires completed by experts and relief workers in flood management.

Among the ML algorithms, the SVM method was selected with 91.37% accuracy. The prioritization program provided by the model, which distinguishes it from other existing models, considers five conditions of the flood occurrence to prioritize actions (season, population affected, area affected, damage to houses and human lives lost). Therefore, the model presents a specific plan for each flood with different occurrence conditions.

The main limitation is the lack of a comprehensive data set to determine the effect of all flood conditions on the prioritization program and the relief activities that have been done in previous flood disasters.

The originality of this paper is the use of ML methods to prioritize administrative measures during and after the flood and presents a prioritization program based on each flood’s conditions. Therefore, through this program, the authority and society can control the adverse impacts of flood more effectively and help to reduce human and financial losses as much as possible.

Flood resilience is a critical concept in flood risk management (FRM). Meanwhile, flood resilience measurement has become vital for making the business case for investment in FRM. However, information is sparse on measuring the level of resilience of flood-prone communities in Nigeria. Therefore, this study aims to develop a fuzzy logic-based model for measuring the resilience of flood-prone communities towards achieving the United Nations Sustainable Development Goals (SDGs) 11 and 13.

This study describes the development of a fuzzy logic-based flood resilience measuring model, drawing on a synthesis of fuzzy logic literature and extant flood resilience. A generalisation of the flood system for a typical Nigerian community was made. It was followed by an identification and characterisation of the variables and parameters of the system based on SDGs 11 and 13. The generated data was transformed into a fuzzy inference system (FIS) using three input community flood resilience dimensions: natural, socio-technical and socio-economic factors (SEF). The model was then validated with primary data obtained from selected flood-prone communities in Ibadan, Southwest Nigeria. Expert opinions were used in rating the input dimensions for the selected communities.

In spite of various inputs from experts in the same study area (Apete, Ibadan, Nigeria), the resulting FIS generated consistent resilience indices for various natural, socio-technical and SEF. This approach can strengthen flood resilience measurement at the community level.

Although previous attempts have been made to measure flood resilience at the individual property level (Oladokun et al., 2017; Adebimpe et al., 2020), this research focuses on measuring flood resilience at the community level by adapting the fuzzy logic approach. The fuzzy logic-based model can be a tool for flood resilience measurement at the community level. It can also be developed further for regional and national level applications.

Because of the global increase of climate change effects, floods are becoming more frequent and severer, especially in urban areas of coastal cities and islands where floodplains have turned into buildings because of rapid urbanisation, leading to a higher risk of damages. Urban heritage areas should be highly considered in the time of evacuation because of the vulnerability of streets and buildings and limitations on taking counteractions. Given these limitations, this study aims to propose a network of potential evacuation routes based on spatial configuration analysis of the heritage areas.

Penang Island's heritage site, namely, George Town, located on the northwest coast of Malaysia, is chosen as the case study. By using an approach of spatial configuration analysis using space syntax techniques in addition to considering the potential starting points for evacuation and flood risk map of the area, this study analysed the area's street network values for evacuation function during flood crisis time.

Potential evacuation routes were identified for flood disasters in the George Town heritage area. Furthermore, the proposed evacuation routes were evaluated in terms of time for evacuation by metric step-depth analysis of space syntax.

A few studies have focused on practical guidelines for evacuation routes based on spatial configuration analysis, an important yet neglected approach in this regard, especially concerning urban island areas. This study can contribute to providing strategies to reduce vulnerability and casualties in urban heritage areas.

Global warming exacerbates sea level rise and extreme weather events that cause severe flooding, resulting in lost productivity and property damage. To reduce the impact of flooding, residents are avoiding purchasing homes in high-risk areas. There are numerous studies on the relationship between flood hazards and housing prices in developed countries, but few in developing countries. Therefore, this study aims to investigate the relationship between flood hazards and housing prices in Hat Yai, Songkhla, Thailand.

This study uses spatial-lag, spatial error and spatial autoregressive lag and error (SARAR) models to analyze the effect of flood risk on property prices. The main analysis examines the degree of flood risk and housing rental prices from our survey of 380 residences. To test the robustness of the results, the authors examine a different data set of the same samples by using the official property valuation from the Ministry of Finance and the flood risk estimated by the Southern Natural Disaster Research Center.

The SARAR model was chosen for this study because of the occurrence of spatial dependence in both dependent variable and the error term. The authors find that flood risk has a negative impact on property prices in Hat Yai, which is consistent with both models.

This study is one of the first to use spatial econometrics to analyze the impact of flood risk on property prices in Thailand. The results of this study are valuable to policymakers for benefit assessment in cost–benefit analysis of flood risk avoidance or reduction strategies and to the insurance market for pricing flood risk insurance.

Despite striving for resilience and a sustainable urban future, European cities face a multitude of crisis caused by both natural and human-induced risks. This paper asks two key questions: How have cities experienced and managed crises situations they encountered? and What are the plans and actions for embedding sustainability at a local level within a clear decision-making structure? Hence, it aims to examine urban resilience in the context of urban crisis and the associated health concerns that took place because of crisis situations, while identifying sustainable urban development initiatives and strategies that were conceived and implemented beyond crisis.

An evidence-based analytical approach is undertaken following two lines of inquiry. The first is case-based and identifies 11 cities that have experienced crisis situations and a further 10 cities that have instigated urban resilience strategies. The second is theme-based and engages with identifying strategies relevant to sustainable urban development at city and project levels. The outcomes of the two lines of inquiry are verified by mapping the lessons learned from the analysis to recent international guidance and a further co-visioning workshop with 6 experts.

The evidence-based analysis reveals key lessons which were classified under two primary types of findings: (a) lessons learned for a future urban resilience resulting from the 1st line of Inquiry (case-based) and (b) lessons learned for a future sustainable urban development resulting from the 2nd line of inquiry (theme-based). The verified lessons provide four areas that can be utilised as key priorities for future urban resilience and sustainable urban development including (a) Governance, effective communication, and decision making for city resilience and urban sustainability; (b) the social dimension of resilience and participatory practices for sustainable urban development; (c) from implicit strategies for health to positive impact on health; and (d) diversification of initiatives and localisation of sustainable development endeavours.

There is always limitation on what a bibliometrics analysis can offer in terms of the nature of evidence and the type of knowledge generated from the investigation. This limitation manifests in the fact that the analysis engages with the body of knowledge but not based on engaging physically or socially with the contexts within which the cases took place or through empirical investigations including systematic observations, focused interviews, and attitude surveys. While the study does not generate empirical findings, the rigour of the bibliometrics analysis offers a credible and reliable evidence on how cities experienced and managed crises situations and their current plans and priority actions for embedding and localising sustainable development measures.

This research conveys significant implications for policy, practice, and action in that it crystalises the view that understanding urban resilience and sustainability, at the city or urban level, requires coupling the two. The findings offer a solid foundation for a more contextualised, evidence-based examination of urban resilience and sustainability during and beyond crisis. Highlighting urban and health challenges that emerged from experienced crisis situations, how these were managed and developing an understanding of sustainable urban development and local resilience strategies elucidate insights that can be adopted and acted upon by city councils and built environment practitioners.

The analysis provides comprehensive insights into urban resilience and sustainable urban development at both city and continental Europe scales in the form of key lessons that represent the first step towards developing rudiments for building a better urban future. Little is known about resilience and sustainability at these scales. The originality of this work lies in the breadth and depth for capturing an inclusive understanding of urban resilience and sustainable urban development based on systematic inquiry and scrutinising the body of knowledge emerged over the past 2 decades.