Urban Resilience Research Articles

Vivid London: Assessing the resilience of urban vibrancy during the COVID-19 pandemic using social media data

Since COVID-19, the focus on urban resilience has intensified, particularly on cities' ability to adapt and recover while maintaining essential functions and liveability; however, few studies have examined the resilience of urban vibrancy during such health crises. This study investigates urban vibrancy resilience in Inner London during the COVID-19 pandemic using multi-sourced social media data (geo-tagged Twitter and Flickr). We propose an analytical framework based on space-time permutation scan statistics (STPSS) to identify spatiotemporal urban areas of interest (ST-AOIs), examining their spatial, temporal, and contextual characteristics. Our findings show that central neighbourhoods with transport hubs, educational and healthcare facilities, eateries, and financial centres exhibit greater resilience. These areas adapt by shifting active periods in response to disruptions. Additionally, we assess the varying resilience capacities of different types of points of interest. This research provides actionable insights for urban planners and policymakers by demonstrating how identifying characteristics of robust urban vibrancy can contribute to the resilience of cities and communities, particularly under normal conditions after COVID-19. The findings offer concrete strategies for integrating social media data into urban planning processes, enabling more responsive and adaptive governance that meets the dynamic needs of urban populations.

Integrating prospect theory and hesitant fuzzy linguistic preferences for enhanced urban flood resilience assessment: A case study of the tuojiang river Basin in western China

The intricate interplay between extreme climatic events and rapid urbanization has compounded the difficulties associated with urban flood resilience, prompting urgent improvements in cities' disaster preparedness and early warning systems. Existing assessment methodologies overlook human factors like decision-makers' psychological biases, hindering precise evaluations of flood defense capabilities. Motivated by the practical need for innovative disaster assessment tools, this study integrates hesitant fuzzy theory with prospect theory. This pioneering approach introduces interval-type indicators into the urban flood resilience assessment framework, establishing a quantitative model to gauge the correlation between urban resilience and various influencing factors. Using the Tuojiang River Basin in western China as a focal point, the research calculates the comprehensive urban flood resilience index for six cities along the Tuojiang River from 2002 to 2021. The findings indicate a consistent upward trajectory in the urban flood resilience index, mirroring government management practices. Notably, Chengdu boasts the highest urban flood resilience index at 1.4288, while Luzhou's index stands at −0.4376, reflecting a shortfall in the expected or desired level within the assessment framework, though without compromising index comparability. Moreover, both cities surpass the regional average of 0.36, categorizing them as high-resilience areas. Significantly, the efficacy of flood defense strategies in these areas correlates positively with economic growth (5.2 %). The model proposed in this study offers a thorough quantification of urban flood defense capabilities, assisting managers in formulating precise disaster mitigation strategies and providing scientific backing for integrated flood disaster management.

The development of resilience research in critical infrastructure systems: A bibliometric perspective.

Critical infrastructure systems (CISs) are the cornerstone of modern cities. Substantial economic losses and social impacts are caused once natural disasters or man-made disruptions attack the CISs. As a "resilient city" has become an essential theme of communities' sustainable development, research on resilience and its practice in industries boost the CISs' capacity to respond and adapt to changing environments. From the Web of Science (WOS) Core Collection, this study screened 1,247 scientific articles related to resilience in CISs and conducted a bibliometric analysis to investigate the evolution and future potential in this field. Topic visualized networks were constructed for CIS resilience using CiteSpace, a dedicated tool for visualizing and analyzing trends and patterns in scientific literature. The results demonstrate collaborative research networks among countries, institutions, main scholar/group networks, and leading journals publishing CIS resilience work. This study also explained how the research interest evolved over the last 20 years and found the current frontiers pointing to "power systems resilience" and "supply chain resilience." The reasons were discussed subsequently from the perspectives of the influence that natural hazards (based on the EM-DAT data) and government policies have upon CISs' resilience work.

Using water and wastewater decentralization to enhance the resilience and sustainability of cities

The imperative to make energy and resource consumption more sustainable is prompting a critical reconsideration of all human endeavours. Within urban water management, the drive to enhance sustainability is grounded in the recognition that water services consume a substantial amount of energy and that wastewater contains valuable resources, including water, heat, organic matter and essential plant nutrients. To make urban water systems more sustainable, a paradigm shift is needed. Among the proposed strategies, source separation coupled with anaerobic co-digestion appears to be an effective means of recovering energy, water and nutrients. Here, as existing centralized infrastructure that serves tens to hundreds of thousands of people is difficult to alter and the technologies needed to realize this strategy are difficult to implement in single-family homes, we consider the scale of a city block. Using a quantitative model of unit processes that simulate energy, water and nutrient flows, we consider the technical and economic feasibility of a representative decentralized system, as well as its environmental impacts. To realize potential synergies associated with on-site use of the recovered resources, we complement the decentralized water system with vertical farming, photovoltaic energy generation and rainwater harvesting. Our analysis suggests that decentralized water systems can serve as a cornerstone of efforts to enhance resource efficiency and improve the resilience of cities.

Efficiency Comparison between Simplified and Advanced Evacuation Analysis Models: A Case Study of Guryong Station, Republic of Korea

Modern subway systems have increased in size and complexity, and this growth presents significant challenges for planners of emergency evacuations. In this study, the effectiveness of the simplified and advanced evacuation analysis methods recommended by the International Maritime Organization (IMO) are evaluated for Guryong Station in Seoul, South Korea. The simplified evacuation analysis method facilitates rapid assessments by using general parameters, while the advanced evacuation analysis entails performing detailed simulations of human behavior and physical interactions. Our findings indicate that the results of the simplified evacuation analysis method are reasonably close to those of the more time-consuming advanced evacuation analysis method, thereby demonstrating the practical applicability of the former method for conducting initial evacuation safety assessments. Specifically, both the simplified and advanced methods showed a 20% reduction in Total Evacuation Time when tunnel evacuation routes were utilized. This finding demonstrates that the simplified method can produce results comparable to the advanced method, making it a reliable tool for initial assessments and for evaluating alternative strategies to reduce evacuation time. By demonstrating that the simplified evacuation analysis method can yield reliable results, we provide valuable insights for developing smart, resilient cities with efficient emergency-response capabilities.

Optimal Scheduling Strategy for Urban Distribution Grid Resilience Enhancement Considering Renewable-to-Ammonia Coordination

The integration of numerous distributed energy sources into the power system offers exciting opportunities to enhance the resilience of distribution networks. It is worth noting that the renewable-to-ammonia system has the potential to alleviate the multi-temporal and spatial imbalance of the power system. Therefore, this paper proposes a mathematical model for a renewable-to-ammonia system, taking into account the material balance and power balance of each unit. Based on this, this paper further explores the optimization scheduling method for flexible ammonia loads in distribution networks. A relaxation method for branch flow models in distribution networks based on second-order cone programming is proposed. An optimization scheduling model for flexible ammonia loads in distribution networks is constructed to minimize network loss. Moreover, considering the environmental advantages of the renewable-to-ammonia system, this paper compares the changes in hydrogen production technologies under different carbon emission constraints. Finally, a case study of the IEEE 33-node system is adopted to verify the effectiveness of the proposed model and method. It indicates that the renewable-to-ammonia system has environmental benefits and can reduce network loss to a certain extent.

Treating the Symptoms as Well as the Root Causes: How the Digital Economy Can Mitigate the Negative Impacts of Land Resource Mismatches on Urban Ecological Resilience

In the era of the digital economy (DE), the traditional economic growth paradigm is no longer applicable. To explore whether the DE can improve the urban ecological problems left behind by rough economic growth, this study examines the effects of land resource mismatch (LRM) on urban ecological resilience (UER) and evaluates the mitigating influence of the DE. This analysis utilizes data from 280 prefectural-level cities in China over the period from 2007 to 2021 and reveals that LRM significantly undermines UER, with this conclusion remaining robust across a series of tests. Additionally, the detrimental impact of LRM on UER is more pronounced in megacities, cities with high levels of economic development, and those with a lower degree of advanced industrial structure. In further analysis, this study finds that the digital economy can optimize the allocation of land resources, thereby enhancing urban ecological resilience, which has the effect of “treating the root causes”. In addition, digital government and digital infrastructure, as key elements of the digital economy, also mitigate the negative impacts of land resource misallocation on urban ecological resilience, having the effect of “treating the symptoms”. Finally, this study proposes policy suggestions such as optimizing ecological layout, deepening land reform, and promoting digital government and infrastructure construction to provide a theoretical basis and practical guidance for local governments to enhance UER and help build a new model of greener, more resilient, and sustainable urban development.

Comprehensive Zoning Strategies for Flood Disasters in China

The frequency of global floods has increased, posing significant threats to economic development and human safety. Existing flood risk zoning studies in disaster prevention lack integration of the natural–economic–social chain and urban resilience factors. This study addresses this gap by constructing flood disaster risk and intensity indices using data from 31 provinces and 295 prefectural-level cities in China from 2011 to 2022. These indices incorporate natural (rainfall), economic (GDP), and social (population, built-up area) indicators to assess the flood likelihood and loss degree, providing comprehensive risk and intensity ratings. The study also examines the impact of resilience factors—environmental (green space), infrastructural (rainwater pipeline density), and natural resource (watershed areas)—on flood intensity. Findings reveal that high-risk regions are mainly in the Yangtze River Basin and southern regions, while high-intensity regions are primarily in the middle and lower Yangtze River and certain northwestern cities. Increasing rainwater pipeline density mitigates flood impacts in high-risk, high-intensity areas, while expanding green spaces and pipelines are effective in high-risk, low-intensity regions. This paper proposes a comprehensive flood hazard zoning mechanism integrating natural, economic, and social factors with urban resilience, offering insights and a scientific basis for urban flood management.

The Urban Geo-climate Footprint approach: Enhancing urban resilience through improved geological conceptualisation

Urban resilience is critical to allow cities to withstand the challenges of the 21st Century. One factor that is often overlooked in such assessments is the role of the subsurface. A novel methodology called the Urban Geo-climate Footprint (UGF) has been developed to classify cities quickly and comprehensively from geological and climatic perspectives. The method operates on the fundamental assumption that cities with similar geological-geographical settings will face similar challenges, due to both common geological issues and associated climate impacts. The UGF approach has been applied to 41 European cities in collaboration with 17 Geological Surveys of Europe, the results of the UGF analysis are presented along with a regional classification of the geological resilience indicators. The UGF tool provides a semi-quantitative representation of the pressures driven by geological and climatic complexity for the cities presented, providing for a first time such classification of the urban environment. The advantage of this methodology lies in increasing awareness among non-experts and decision-makers of the interplay between geological settings, climate change pressures, and anthropogenic activities. Furthermore, it facilitates the exchange best practices among city planners to increase resilience, supporting knowledge based decision making to promote actions and policies, that enhance geoscience-informed climate justice.

Global scale assessment of urban precipitation anomalies

Urbanization has accelerated dramatically across the world over the past decades. Urban influence on surface temperatures is now being considered as a correction term in climatological datasets. Although prior research has investigated urban influences on precipitation for specific cities or selected thunderstorm cases, a comprehensive examination of urban precipitation anomalies on a global scale remains limited. This research is a global analysis of urban precipitation anomalies for over one thousand cities worldwide. We find that more than 60% of the global cities and their downwind regions are receiving more precipitation than the surrounding rural areas. Moreover, the magnitude of these urban wet islands has nearly doubled in the past 20 y. Urban precipitation anomalies exhibit variations across different continents and climates, with cities in Africa, for example, exhibiting the largest urban annual and extreme precipitation anomalies. Cities are more prone to substantial urban precipitation anomalies under warm and humid climates compared to cold and dry climates. Cities with larger populations, pronounced urban heat island effects, and higher aerosol loads also show noticeable precipitation enhancements. This research maps global urban rainfall hotspots, establishing a foundation for the consideration of urban rainfall corrections in climatology datasets. This advancement holds promise for projecting extreme precipitation and fostering the development of more resilient cities in the future.

Research on the Factors Influencing the Epidemic Resilience of Urban Communities in China in the Post-Epidemic Era

In the aftermath of the COVID-19 pandemic, people are gradually realizing that urban community resilience is pivotal for effectively managing public health emergencies. This study employed grounded theory to establish a theoretical framework for epidemic resilience of urban communities (ERUC) in the post-pandemic era. Subsequently, the decision-making trial and evaluation laboratory (DEMATEL)-interpretive structural modeling (ISM) method is utilized to discern the significance and hierarchical interrelations among influencing factors. The findings delineate that 14 determinants shaping ERUC are organized into five distinct tiers. Notably, nine determinants emerge as principal: vulnerable group; educational attainment; risk perception; medical insurance coverage; communal norms; community emergency response; community services; resident participation; and government efficacy. Among these, the vulnerable group and government efficiency are identified as foundational factors, while medical insurance coverage, resident participation, and community infrastructure are identified as direct influences.

Artificial intelligence for enhancing resilience

In an increasingly complex and unpredictable world, resilience-the ability to withstand and recover from adverse conditions is essential across various sectors. This research paper investigates the transformative potential of artificial intelligence (AI) in enhancing resilience across multiple domains. We explore how AI technology can be utilized to develop resilient infrastructure, providing advanced predictive maintenance and real-time monitoring capabilities that ensure robustness and longevity. The study examines the role of AI in improving disaster response, offering rapid data analysis and decision-making support to enhance emergency management outcomes. In climate change, AI-driven strategies are assessed for their effectiveness in fostering climate resilience, including predictive modeling of extreme weather events and optimizing resource allocation. The paper also discusses AI applications in healthcare resilience, such as enhancing diagnostics, patient care, and operational efficiency during crises. Business continuity and crisis management are examined, highlighting AI's capability to anticipate disruptions and maintain operational stability. The paper emphasizes the importance of strengthening cybersecurity resilience using AI to detect and mitigate threats proactively. AI's role in enhancing community and social resilience is analysed, particularly in supporting vulnerable populations and fostering social cohesion. Additionally, we explored AI-powered solutions for urban resilience, focusing on smart cities and sustainable development. The study also covers AI's contributions to environmental and ecological resilience, resilient supply chain management, and resilience in the hospitality and tourism industry. Finally, we investigated AI's potential in fostering psychological resilience, providing personalized mental health support and stress management tools. Through these diverse applications, the paper underscores AI's critical role in building a resilient future.

Exploring the network structure of coupled green-grey infrastructure to enhance urban pluvial flood resilience: A scenario-based approach focusing on ‘centralized’ and ‘decentralized’ structures

Urban pluvial floods pose a significant risk to cities, occurring when precipitation exceeds the carrying capacity of the urban drainage network. Coupled green-grey infrastructure has emerged as a sustainable solution for mitigating urban pluvial floods. This study aims to explore best practices in the network configuration of urban drainage systems coupled with low-impact development (LID) to enhance flow distribution and stormwater infiltration. To do so, we focused on two competing key concepts in network analysis: (1) Centralization and (2) Decentralization. We integrated a one-dimensional stormwater model with a rapid flood spreading model to assess the flood mitigation performance of various centralized and decentralized network configurations in the Gangnam region of Seoul, South Korea. To further assess the combined effects of green and grey infrastructure, we compared the performance of each drainage network configuration with and without identical mixed LID practices. Here we show that the centralized drainage network scenario performed best in reducing flood volume by 40.3%, the decentralized drainage network scenario performed best in shortening flood duration by 47.8%, and the LID practices scenario performed best in mitigating peak flooding rates by 4.2%, each as independent scenarios. When all three scenarios were coupled together, flood volume could be reduced by 73.5%, flood duration by 54.7%, and peak flooding rates by 19.8% in the study area. This exploratory study underscores the potential of network analysis in urban flood research, particularly the effectiveness of loosely-connected network topology. Our findings contribute to the development of best practices for coupled green-grey infrastructure, facilitating sustainable stormwater management and urban flood resilience.

On mapping urban community resilience: Land use vulnerability, coping and adaptive strategies in Ghana

Cities across the globe are prioritizing resilience in the wake of increasing climate change-related disasters. About 44% of these disasters are floods and their manifestation in cities is more pronounced, threatening urban social, ecological, and economic systems. This study draws on community resilience and participatory GIS, to examine land use vulnerability to flooding and local coping and adaptive strategies to achieve resilience. Using Ghana as a case study, the results show that participatory mapping offers community resilience benefits by providing context to community resilience challenges and potentials, enabling a deeper understanding of socio-environmental coupling that contributes to flood vulnerability and builds on community adaptive strategies through harnessing local community knowledge. We identified that topography, poor drainage and road network, rainfall variability, residents’ land use practices, and land use planning conundrum drive disparities in land use vulnerability to flooding. Participants underscored the necessity of critical urban infrastructure in facilitating community adaptability to floods. The findings indicate that socio-spatial inequities threaten urban community resilience, especially in increasingly cosmopolitan urban contexts, by putting the marginalized urban population in a more vulnerable position. We recommend the prioritization of recognitional equity in community resilience planning efforts to allow for the targeting of resilient interventions that reflect and respect social differentiation in the urban environment so that outcomes will not exacerbate or generate new urban socio-spatial inequalities.

Booster or inhibitor: Diagnosing effects of low-carbon pilot city policies on urban resilience from the perspectives of heterogeneity, mechanisms and spillover

Low-carbon city pilot policies are crucial for addressing urban challenges, alleviating pressure on urban systems, and encouraging sustainable development and resilience. This study focused on Chinese cities to explore how low-carbon city pilot policies influence urban resilience. The impact of the policies on urban resilience was assessed using difference-in-differences, mediating effect, and moderating effect models, showcasing both the variation and mechanism of the effects. The results are as follows: First, the introduction of low-carbon city pilot policies has resulted in a 9.3% increase in urban resilience, with noticeable enhancements over time. Second, the influence of low-carbon city pilot policies on urban resilience demonstrates heterogeneity, particularly with more pronounced effects observed in the eastern and coastal regions, as well as in resource-based, priority, and large cities. Third, the implementation of low-carbon city pilot policies has bolstered urban resilience through the promotion of technological innovation, the transformation of industrial structures, and the improvement of energy composition, with green production having a beneficial moderating function. Fourth, low-carbon city pilot policies have a siphoning effect on urban resilience within 50 km, and a positive spatial spillover effect between 50 and 200 km, both of which diminish with increasing distance. Finally, the examination of the policy implications derived from the study's findings is addressed. This study has the potential to serve as a valuable reference for formulating urban sustainable development strategies.

Machine Learning for Blockchain and IoT Systems in Smart Cities: A Survey

The integration of machine learning (ML), blockchain, and the Internet of Things (IoT) in smart cities represents a pivotal advancement in urban innovation. This convergence addresses the complexities of modern urban environments by leveraging ML’s data analytics and predictive capabilities to enhance the intelligence of IoT systems, while blockchain provides a secure, decentralized framework that ensures data integrity and trust. The synergy of these technologies not only optimizes urban management but also fortifies security and privacy in increasingly connected cities. This survey explores the transformative potential of ML-driven blockchain-IoT ecosystems in enabling autonomous, resilient, and sustainable smart city infrastructure. It also discusses the challenges such as scalability, privacy, and ethical considerations, and outlines possible applications and future research directions that are critical for advancing smart city initiatives. Understanding these dynamics is essential for realizing the full potential of smart cities, where technology enhances not only efficiency but also urban sustainability and resilience.

Urban Flood Resilience Evaluation Based on Heterogeneous Data and Group Decision-Making.

In recent years, urban floods have occurred frequently in China. Therefore, there is an urgent need to strengthen urban flood resilience. This paper proposed a hybrid multi-criteria group decision-making method to assess urban flood resilience based on heterogeneous data, group decision-making methodologies, the pressure-state-response model, and social-economic-natural complex ecosystem theory (PSR-SENCE model). A qualitative and quantitative indicator system is formulated using the PSR-SENCE model. Additionally, a new weighting method for indicators, called the synthesis weighting-group analytic hierarchy process (SW-GAHP), is proposed by considering both intrapersonal consistency and interpersonal consistency of decision-makers. Furthermore, an extensional group decision-making technology (EGDMT) based on heterogeneous data is proposed to evaluate qualitative indicators. The flexible parameterized mapping function (FPMF) is introduced for the evaluation of quantitative indicators. The normal cloud model is employed to handle various uncertainties associated with heterogeneous data. The evaluations for Beijing from 2017 to 2021 reveal a consistent annual improvement in urban flood resilience, with a 14.1% increase. Subsequently, optimization recommendations are presented not only for favorable indicators such as regional economic status, drainability, and public transportation service capacity but also for unfavorable indicators like flood risk and population density. This provides a theoretical foundation and a guide for making decisions about the improvement of urban flood resilience. Finally, our proposed method shows superiority and robustness through comparative and sensitivity analyses.

A novel ANN-CA and MCDA integrated framework for predicting urban expansion and its implications on future flood risk, Accra Metropolis

Urban development in African countries significantly impacts environmental sustainability and city resilience, particularly in flood risk management. The Accra Metropolis, in particular, faces increasingly prevalent annual floods that disproportionately affect the urban poor living in informal settlements, resulting in significant loss of life and disruption of livelihoods. This study developed a GIS-based flood risk mapping framework that integrates artificial neural network (ANN) and cellular automata (CA) modelling with multi-criteria decision analysis. This hybrid approach was employed to predict flood scenarios for the Metropolis in 2032 and 2042. The framework incorporated six hydro-geomorphological indicators influencing extreme events: LULC, slope, elevation, drainage density, soil type, and proximity to rivers. The study analysed LULC projections, revealing a trend of substantial urban expansion with an estimated 10.9% increase in built-up areas within the next 20 years. This growth is expected to significantly heighten future flood risk in both the central upstream and downstream portions of the Metropolis, particularly in low-lying informal settlements close to the Odaw River and Korle Lagoon. Model performance was validated by ROC curve analysis, with AUC values of 0.927 and 0.922 for 2032 and 2042, respectively, which resonates with the records of previous flood distribution studies of the area. This study highlights the crucial need for sustainable urban development, improved infrastructure, and proactive flood mitigation measures in Accra to assist urban planners, policymakers, and stakeholders in managing flood risks effectively.

Crossed by the border: children’s lived experiences with flooding in an urbanized transborder watershed

ABSTRACT This article analyzes the differential effect of the US-Mexico border on the lived experience of children exposed to flooding risk in an urbanized transborder watershed. The central argument is that this geopolitical border is an institution generative of social and spatial processes that create and thrive on differences and expose children on both sides of the border to high but unequal hazard levels. We pose that children’s bifurcated experiences with rain evince the border’s structuring power as a supra institution producing a socio-spatial regime that enables environmental inequities producing disparate representations of place. Understanding children’s lived experiences is critical to reducing their vulnerability in a highly integrated cross-border urbanization. Framed as a case study based on qualitative data obtained through narratives and visual elicitation techniques, the analysis reveals children’s experiences with flooding and associated hazards that have not been exposed in prior border research and have important implications for integrated disaster management, environmental justice, and resilience in border regions and cities.

Urban Lake Health Assessment Based on the Synergistic Perspective of Water Environment and Social Service Functions.

Urban lakes serve as vital ecological and recreational anchors within built environments, essential for enhancing urban resilience. Evaluating lake health predominantly focuses on water quality, assessing indicators such as nutrient levels, toxicity, pH balance, and water clarity to monitor changes. This study proposes a comprehensive evaluation framework that systematically describes specific spatiotemporal manifestations and periodic exogenous regulation characteristics across five dimensions: physical structure, water quality, shoreline dynamics, external regulation, and social service. Furthermore, it introduces an urban lake health assessment model based on synergistic development to evaluate the integrated development and interaction between water environments and social services. This model is applied across urban lakes in various developmental stages in China. Key findings include: 1) Urban development often impacts lake health disparately, with varying degrees of synergy observed between water environments and social services across different urban lakes. However, shifts in urban ideologies and improvements in governance, along with protective policies and project implementations, have contributed to improving water quality to some extent. 2) Engineering interventions do not consistently correspond with improvements in water quality, and governance measures sometimes yield mixed outcomes, underscoring the necessity for systematic solutions to lake health. Restoring hydrological processes emerges as crucial for enhancing sustainability.