Systematic Literature Review: Research Development of Urban Resilience in Metropolitan Areas
Abstract
1. Introduction
- Integration: The metropolitan area is not just a collection of settlements but functions as a single system.
- Core–periphery structure: There is a dominant central city (or cities) surrounded by smaller towns and suburbs.
- Functional ties: These include economic links (e.g., labor market integration), social networks and infrastructure connections (e.g., transportation and services).
- The capacity to absorb stress or disruptive forces through resistance or adaptation.
- The capacity to manage, or maintain, certain basic functions and structures during a hazardous event.
- The capacity to recover or “bounce back” after an event.
- How has urban resilience research in metropolitan areas developed over the years, and which topics have been widely discussed and cited in research related to this theme?
- What types of shocks occur, and on which continents do they occur in metropolitan areas?
- What research methods, spatial scales, and indicators are used to measure and evaluate urban resilience in metropolitan areas?
2. Materials and Methods
- The database search focused on collecting articles related to urban resilience in metropolitan areas or megacities. Each search began with a search for the article title or keywords “urban resilience,” followed by the abstract title or keywords containing the words “in metropolitan” OR “megacity” OR “megacities.”
- The search results from the SCOPUS database, which is limited to the fields of social and environmental science, yielded 924 articles. Furthermore, duplications were identified using the Zotero application (version: 7.0.22 (64 bit)), which efficiently manages, stores, and cites research sources. From this application, two articles that had duplicates were obtained, so the number of articles ready to be filtered was 922. Furthermore, using Microsoft Excel, the articles were checked using the criteria for the suitability of the title to the topic to be discussed, which was limited only to those in English; 401 articles were obtained in the form of journals or books. Filtering was continued by examining the suitability of the abstract content and the availability of open-access journals. The final number of articles reviewed was 248.
- A total of 248 articles were reviewed by creating a list of information categories from journals referring to the research questions. The information needed, in addition to that already provided by SCOPUS in the form of year of publication, number of citations per year, author’s name, and information from the results of the article review, was also added in the form of type of the shock, spatial scale, research approach method, resilience dimensions, analysis used, indicators used, study location, and research results.
3. Results
3.1. Keyword Correlations on Urban Resilience in Metropolitan Areas
3.2. The Development of Urban Resilience Research Topics in Metropolitan Areas in the World from Year to Year
The Number of Citations in Scopus | Title | Authors | Number of Quotes per Year |
---|---|---|---|
1 | Sustainable-smart-resilient-low carbon-eco-knowledge cities; Making sense of a multitude of concepts promoting sustainable urbanization | [27] | 7950 |
2 | Urban flood resilience. A multi-criteria index to integrate flood resilience into urban planning | [35] | 6167 |
3 | Home gardening and urban agriculture for advancing food and nutritional security in response to the COVID-19 pandemic | [31] | 5920 |
4 | Flood risk assessment in metro systems of mega-cities using a GIS-based modelling approach | [36] | 4886 |
5 | Resiliency assessment of urban rail transit networks: Shanghai metro as an example | [32] | 2743 |
6 | Resilient cities: Meaning, models, and metaphor for integrating the ecological, socio–economic, and planning realms | [28] | 2700 |
7 | Urban—Rural Differences in Disaster Resilience | [30] | 2467 |
8 | System dynamics modelling for improving urban resilience in Beijing, China | [29] | 2280 |
9 | Green and cool roofs to mitigate urban heat island effects in the Chicago metropolitan area: Evaluation with a regional climate model | [34] | 2244 |
10 | Evicting slums, ‘building back better’: Resiliency revanchism and disaster risk management in Manila | [33] | 1783 |
11 | Heat vulnerability caused by physical and social conditions in a mountainous megacity of Chongqing, China | [37] | 1733 |
12 | Exploring the spatial–temporal dynamics of ecosystem health: A study on a rapidly urbanizing metropolitan area of Lower Gangetic Plain, India | [41] | 1725 |
13 | Spatial–temporal variation, driving mechanism and management zoning of ecological resilience based on RSEI in a coastal metropolitan area | [40] | 1600 |
14 | Steps toward a resilient circular economy in India | [38] | 1575 |
15 | Adaptation responses to climate change differ between global megacities | [42] | 1567 |
16 | Analyzing the level of accessibility of public urban green spaces to different socially vulnerable groups of people | [43] | 1557 |
17 | Assessing urban landscape ecological risk through an adaptive cycle framework | [39] | 1529 |
18 | Modelling pedestrian emotion in high-density cities using visual exposure and machine learning: Tracking real-time physiology and psychology in Hong Kong | [44] | 1250 |
19 | From the smart city to the smart metropolis? Building resilience in the urban periphery | [45] | 1167 |
20 | Equality of access and resilience in urban population-facility networks | [46] | 1067 |
3.3. Identification of Spatial Scales, Research Methods, and Indicators for Urban Resilience Assessment in Metropolitan Areas
4. Discussion
4.1. Urban Resilience Research Trends in Metropolitan Areas
4.1.1. Review: Correlation Between Keywords
4.1.2. Review: Highly Cited Research
4.1.3. Review: The Types of Shocks That Occurred
4.2. Urban Resilience in Metropolitan Asia and Resilience Research Challenge
4.3. Selection of Research Methods, Spatial Scales and Indicators in Measuring Urban Resilience
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
Dimension | Spatial Scale | Shock | Analysis | Indicator | References |
---|---|---|---|---|---|
Socio-Economic | Community | Climate Change | Factors that influence | Age, generation group, education, income | [74] |
Regional and city | Earthquake, climate change and COVID-19 | Descriptive analysis and trends | Poverty, multidimensional poverty, potential lives lost, infant mortality, municipal expenditure, COVID-19 infected, COVID-19 deaths | [110] | |
City | Opioid overdose crisis | Resilience index or vulnerability index | Observed versus predicted opioid overdose mortality rates, availability of health and social services, community mobilization efforts, and community attitudes toward addiction. | [111] | |
City | Natural Disasters | City resilience index | Population census, financial independence ratio, local tax revenues, percentage of economically active population, population, percentage of population over 65 years of age | [112] | |
City | Economic downturn and outmigration | Economic resilience index | Diversity (industrial diversity and industrial transformation), income and expenditure related capabilities (community and government income and expenditure), innovation environment (environmental technological innovation, environmental ecological development, basic social environment), Development trends (economic and social development trends) openness (openness to domestic and foreign trade) | [113] | |
Economic | City | COVID-19 Pandemic | City resilience index | GDP per capita, proportion of tertiary industry in GDP, realization of foreign capital utilization, urban per capita income, income in the general public budget | [114] |
City | Economic recession | Economic capacity, socio–demographic capacity, and connectivity capacity Community | Income equality, economic diversity, affordability, business environment, educational attainment, health insurance rates, civic infrastructure, metropolitan stability, and voter turnout. | [115] | |
City | Economic fluctuations | Temporal development of urban resilience | GDP per capita, GDP growth rate, total fixed asset investment | [116] | |
City | natural disasters (rain, storm, typhoon) | urban resilience index | employment rate of population aged 16 and over, GDP per capita, Public budget expenditure, total value of industrial output by district, urban GDP by district | [117] | |
City | Natural disasters | Urban and rural resilience index | Home ownership, employment rate, racial/ethnic income equality, primary sector/tourism independence, gender income equality, business size, large-scale distribution retail-regional, federal employment | [30] | |
City | COVID-19 | Urban resilience index | Annual GDP, Regional budgeted expenditure, Proportion of tertiary industry in GDP, Scientific operational cost, Total local tax revenue, Actual foreign investment, End of year savings balance for urban and rural resilience | [57] | |
City | Rapid urbanization | City resilience index | GDP per capita, City income, Actual amount of foreign investment used in a year, Ending of year-end savings balance of urban and rural population, Non-agricultural employment ratio (%) | [118] | |
City | Climate change | Urban resilience index | GDP per capita, government fiscal expenditure per capita, urbanization rate, population density in built-up areas, percentage of economic losses due to climate disasters in GDP, urban disposable income per capita | [73] | |
Social | Local | Flood | Resilience index | Population density, per capita income, inadequate sanitation | [58] |
District | Floods | Influencing factors | Human (population density, age, ethnic disparities, disability), community (health access, population well-being, migration), organization (administrative work, regional accessibility, housing capacity) | [61] | |
City | water drought | City blueprint Approach consists of: Trends and Pressures Framework (TPF) | TPF = social pressure (urbanization rate, disease burden, education level, political instability), | [119] | |
City | social disparities | Temporal development of city resilience | number of hospital beds per 10,000 people, number of higher education students per 10,000 people, registered unemployment rate in urban areas | [116] | |
City | natural disasters (rain, storms, typhoons) | City resilience index and analysis of inhibiting | population aged 60 years and over and under 17 years, population density, number of volunteer groups, health technicians, area of administrative division, area per capita | [117] | |
City | Natural disasters | Urban and rural resilience | Index of equality of achievement in education, pre-retirement age, access to transportation, communication capacity, English language competence, people with non-special needs, Health insurance, Mental health support, food supply capacity, access to doctors | [30] | |
City | COVID-19 pandemic | City resilience index | Number of students on campus, number of beds in health facilities, percentage of non-agricultural employment, registered urban unemployment rate | [114] | |
City | COVID-19 pandemic | City resilience index | Population density, number of unemployed (registered) in urban areas, number of public administration practitioners, number of university students, number of doctors in the public health system, average number of employees working, number of people covered by basic health insurance | [57] | |
City | Rapid Urbanization | City resilience index | Number of students in regular schools and universities, number of hospital beds per 1000 population | [118] | |
City | Climate change | City resilience index | Ability for social development, percentage of population receiving natural disaster relief funds, expectations life, insurance penetration and density, proportion of vulnerable population (<16 or >60 years), proportion of population with minimum standard of living, percentage of population with pension income and property, number of resilient communities | [73] | |
Ecological | City | Urbanization | ecological resilience index | pollution load, environmental quality, landscape form | [120] |
City | water shortage | Ecological resilience index (resistance, adaptability, resilience), influencing factors, evaluation and spatiotemporal evolution of water poverty characteristics | resistance (secondary industry added value/GDP, tertiary industry added value/GDP, GDP per capita, natural population growth rate, proportion of science and technology expenditure to public budget expenditure), adaptability (industrial smoke and dust emissions, industrial sulfur dioxide emissions, centralized household waste treatment rate) Resilience (drainage pipe length, volume of urban solid waste disposal, green open space area of parks, green coverage rate in built-up areas, fiscal self-sufficiency rate, green open space area of parks per capita) | [62] | |
City | rapid urbanization | ecological network resilience (ecological resistance, network analysis index) | land use type, vegetation cover, geographic feature information | [121] | |
City | urbanization and climate change | urbanization and climate change landscape ecological risk assessment (LERA): potential, connectivity and resilience | potential (vegetation coverage, temperature, brightness, rainfall erosivity, night light intensity) connectivity (landscape diversity, integral connectivity index, distance to construction land, road network density) resilience (vegetation cover trends, night light intensity trends) | [39] | |
City | water drought | The City Blueprint Approach consists of: Trends and Pressures Framework (TPF), City Blueprint Performance (CBF), Governance Capacity Framework (GCF) | TPF = environmental pressures (floods, water scarcity, water quality, heat risk) 2. CBF (water quality, solid waste, basic water services, wastewater treatment, infrastructure, climate resilience, governance) | [119] | |
City | increasing population density, flooding | impact on population growth, built-up area expansion, infrastructure pressure, flood risk exposure, and loss of agricultural land until 2050 | percentage of population increase, built-up area growth, population density, conversion of agricultural land area, and number of people exposed to flood risk zones. | [122] | |
City | ecological degradation | Temporal development of urban resilience | green coverage level of built-up areas, green area of parks per capita, level of non-hazardous domestic waste treatment | [116] | |
City | natural disasters (rain, storm, typhoon) | Urban resilience index and analysis of inhibiting factors | number of regional parks, green area of parks, green area of green space, river area | [117] | |
City | Natural disasters | City and village resilience index | Local food suppliers, natural flood buffers, efficient energy use, permeable surfaces, efficient water use | [30] | |
City | Natural disasters | City resilience index | Percentage of residential area, percentage of industrial area, percentage of commercial area, population density, percentage of housing permitted before 1985, percentage of area with disaster prevention facilities and installations | [112] | |
City | COVID-19 pandemic | City resilience index | Level of green coverage in built-up urban areas, public green areas per capita, volume of industrial wastewater discharged, level of non-hazardous household waste disposal | [114] | |
City | COVID-19 pandemic | City resilience index | Green areas, green coverage in built-up areas, public green areas, land area, industrial wastewater discharge, industrial sulfur dioxide emissions | [57] | |
City | Rapid urbanization | City resilience index | Coverage level of green open space in built-up areas, Area of green open space parks per capita, Wastewater discharge per capita | [118] | |
City | Climate change | City resilience index | Ratio of environmental expenditure to fiscal expenditure, percentage of green forest area (or green area per capita in urban areas), | [73] | |
Physical/Infrastructure | Local | Floods | Resilience index | Flood depth and flood duration factors | [58] |
City | traffic congestion | congestion index to assess traffic vulnerability and resilience of transportation systems | traffic volume (vehicles/hour), degree of saturation (ratio), and congestion index | [123] | |
City | Flood | Impact of flood policy, governance, and urban planning on flood resilience | flood elevation, urban expansion, population growth, river width changes, and topography | [124] | |
City | Infrastructure vulnerability | Temporal development of urban resilience | road area per capita, gas penetration rate, drainage pipe density | [116] | |
City | natural disasters (rain, storm, typhoon) | Urban resilience index and analysis of inhibiting factors | drainage pipe maintenance management assessment score, pipe sludge per unit length, inspection score of operation and maintenance of drainage pump stations, number of health institutions, number of hospital beds, number of waste management installations in the service area | [117] | |
City | Natural disasters | Urban and rural resilience index | More robust housing type, availability of temporary housing, medical care capacity, evacuation routes, quality housing stock, temporary shelters, school restoration potential, industrial resupply potential, high-speed internet infrastructure | [30] | |
City | Climate change | City resilience index | Ability to manage urban risks, waterlogging points in urban areas, traffic congestion index, public health facilities per capita, broadcasting and television coverage | [73] | |
City | Natural Disasters | City resilience index | Average degree of land slope, average land height, percentage of river or tributary areas, percentage of land 10 m below sea level, daily rainfall intensity level | [112] | |
City | COVID-19 pandemic | City resilience index | Urban road area per capita, urban drainage pipe density, annual electricity consumption, goods traffic on highways, Internet broadband access users | [114] | |
City | COVID-19 pandemic | City resilience index | Number of hospitals and health centers, number of beds in hospitals and health centers, actual road area, volume of highway transportation, total annual electricity supply, total annual water supply | [57] | |
City | Rapid urbanization | City resilience index | road area per capita, gas supply per capita, number of buses per 10,000 population, length of drainage pipes per capita, proportion of international internet users | [118] | |
Local | COVID-19 pandemic | Potential risk location of transmission | Number of buildings with size <90 m2 per sub-district, number of buildings with size 90–300 m2 per sub-district, number of buildings with size >1000 m2 per sub-district, population density, number of intersections per sub-district, distance from train station | [63] | |
Local | COVID-19 pandemic | Consistency Index and consistency ratio | 1. public transportation (route, station penetration, social distance, occupancy; 2. green-blue infrastructure (walkability, activity range, basic functionality, green infrastructure) 3. Public buildings and facilities (building type, mixed use, open space, ventilation and lighting) 4. Health service organization (patient capacity, facility location, equipment and supplies, infection control capacity) 5. policy management (citizen participation, effectiveness of handling capacity, information sharing) | [59] | |
Institutional | City | climate change | institutional capacity assessment | engagement, mainstreaming, monitoring and evaluation, investment, information, knowledge, innovation and learning, skills and expertise, local content sensitivity, implementation | [125] |
City | Hurricane | CERNL’s role in rebuilding basic services and infrastructure, assessing the effectiveness of the board in a fragmented institutional framework | speed of service recovery, level of infrastructure repair, level of stakeholder participation, and functionality of governance structures during the recovery process | [52] | |
City | water drought | City blueprint Approach consists of: Governance Capacity Framework (GCF) | awareness, useful knowledge, continuous learning, stakeholder engagement process, management ambition, change agents, multi-level network potential, financial feasibility and capacity implementation | [119] | |
City | institutional weaknesses | Temporal development of city resilience | number of social security participants, number of community service facilities, number of public management employees and social organizations | [116] | |
City | Natural disasters | City and village resilience index | Mitigation expenditure, flood insurance coverage, jurisdictional coordination, disaster relief experience, local disaster training, performance regime (nearest metro area or state/capital), population stability, nuclear power plant accident planning, agricultural insurance coverage | [30] |
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Dimension | Descriptions |
---|---|
Social | The ability of a group or community to overcome external pressures and disturbances resulting from social, political and environmental change [19] through access to capital and creating opportunities to face threats [20]. |
Economic | The ability of a socio–economic system to withstand shocks, recover from crisis situations after the crisis has ended, and continue to adapt [21] to external changes independently [22]. |
Infrastructure and ecosystem/environment | The ability of quality infrastructure and ecosystems to protect, provide and connect communities during times of shock [15]. |
Institutional | The ability of all types of institutions and key actors to continuously adapt to changing conditions, including the ability to respond to negative phenomena [23]. |
Type of Shocks | Descriptions | Example |
---|---|---|
Economic | Disrupts the supply chain by reducing demand | 2008 Financial Crisis, 2020 Economic Crisis |
Institutional | Instituional change that changes the economic landscape | Brexit, COVID-19 policies, North American Free Trade Agreement (NAFTA) |
Organizational | Changes in industrial structure due to foreign competition alter global supply chains | Change in labour laws and consumption preference |
Environmental | Disrupts the supply chain by halting production | Earthquakes, floods, climate change, forest fires |
Man-made | Disrupts the supply chain by halting production | Terrorist attacks |
Technological | Disruptive technology that changes the economic landscape disrupting global supply changes | Steam engine, blockchain technology |
Epidemic | Alters the economic landscape and disrupts the supply chain by halting production | COVID-19, severe acute respiratory syndrome (SARS), Ebola pandemics |
Spatial Scale | Resilience Research Focus |
---|---|
Global | Limitations on disaster reduction and adaptation to climate change. |
National | In addition to climate change, attention is also directed toward a country’s macroeconomic aspects—such as economic growth, labor market conditions, and economic competitiveness—as well as infrastructure development. |
Regional | Focus on economic structure, economic interdependence, or levels of innovation between regions. |
Urban (city/metropolitan) | Socio-ecological approach, focusing on the ability of infrastructure to withstand natural disasters, local economic adaptation, inclusion and integration of local communities. |
Suburban (local/community) | Focus on issues of segregation, cohesion and social networks. |
Household/Individual | Focus on human capital, physical and mental health in the face of threats. |
No | Disaster Factors | Type of Shock | Metropolitan Asia | Metropolitan North America | Metropolitan South America | Metropolitan Europe | Metropolitan Africa | Metropolitan Australia and New Zealand |
---|---|---|---|---|---|---|---|---|
1 | Non-Nature | Economic | economic depression (3), socio–economic disparities, food security, housing challenges, economic pressures/fluctuations (5), socio–economic changes, rising oil prices, | aging population, financial insecurity and inequality/economic inequality (2), food insecurity (2), economic recession (3) | economic crisis, transition economy, deindustrialization | economic crisis (7), food security, transition economy (3) | socio–economic pressures | food security, rising oil prices, socio–economic pressures |
Institutional | Decentralization | Decentralization | Institutional transformation, city policy, decentralization | - | ||||
Technology | public transportation network (3), use of technological devices, infrastructure failure, airport closures, urban rail transit disruption, technological shifts, food availability disruption | public transportation | use of e-mobile applications, public transportation, automation and advanced technology | - | Public transport | |||
Medical | resource organization, political instability | |||||||
2 | Humans | Human creative/artificial | Human urban stress (2)/external shock/mental health (2), urbanization (10), land use change (5), congestion/pollution (3), population density (2) | urbanization (4), opioid overdose, social inequality and racism | Land use change | urban sprawl, congestion, urbanization (3) | urbanization (4), child displacement, congestion | |
3 | Nature | Environment | floods (26), climate change (16), environmental stress (3), drought/water shortage (4), extreme storms (2), natural disasters (5), landslides(3), tsunamis, urban heat (4), sea level rise, earthquakes (2), typhoons, energy vulnerability, wetlands | hurricane, tornado, snowstorm, climate change (8), urban heat (3), flood (2), decrease in water flow, natural disaster (3) | Floods (5), earthquakes (4), climate change(2), extreme weather, heat waves, landslides (2), tsunamis (2), drought, hurricane, environmental stress | sea level rise, climate change (9), energy crisis, volcanic eruptions, ecological change, earthquakes, floods (5), heat waves, environmental service degradation | extreme heat (3), natural disasters, floods (3), climate change, drought, sea level rise | Earthquakes, loss of biodiversity, environmental stress and ecological degradation |
Epidemic | COVID-19 (6), epidemic disaster, infectious disease | COVID-19 (2) | COVID-19 (2) | COVID-19 (9) | COVID-19 | COVID-19 |
Forms of Analysis in Research Methods | Spatial Scale | References |
---|---|---|
| City City/Metropolitan Metropolitan Community Regional/National Case study | [48,49] [45,50,51] [52] [53] [54,55] [56] |
| City, local City, case study City, District Metropolitan, city City, Community Case study City | [57,58,59] [39,60] [61,62] [63,64,65,66] [67,68] [69,70] [29,71,72] |
| City Communities Metropolitan Metropolitan | [73] [74] [75] [76] |
Forms of Resilience | Urban System Performance | Urban System Capacity |
---|---|---|
Review | The results of regional reactions to shocks, assess the response of a region (resistance, resilience or non-resilience) or how resilient the region is compared to another. | Empirically examined the adaptive capacity of regional resilience by examining changes in the system (structure and function) experienced by a region after a shock occurs. |
Approach of methodology | Deterministic (quantitative) Advantage: Can explain whether it is resilient or not and why it has resilience. (what are the forms and determining factors of resilience) Disadvantage: The type of resilience cannot be clearly interpreted. | Heuristic (qualitative) Advantage: Can interpret types of resilience (engineering, ecological, evolutionary and transformative) clearly, Disadvantages: It cannot determine whether an area is resilient or not. |
Suggestion: using mixed-method approach combines the strength of deterministic (quantitative) and heuristic (qualitative) approaches to answer whether it is resilient, why and how its vulnerability or resilience occurs | ||
Analysis Method | Benchmarking or counterfactual, such as resilience index measurement, influencing factors, impact measurement, temporal resilience | Causal mechanisms or policy implications, descriptive analysis of case studies, |
Spatial Scale | Generally in the city, regional and national scale, few in the local scale | Generally in the local scale, society/community |
Dimensions/Issues discussed | Regional and national scale: climate change, economic dimension City/local scale: socio–ecological, economic and infrastructure dimension | Local/community scale: wealth, income, livelihoods, well-being, inclusion and integration of local/community issues Regional/national scale: institutional dimension |
Indicator | The driving factors/driver/driving axis of each dimension/issue is discussed so that critical points that influence the level of resilience of a region can be identified. |
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Saptono, Y.; Rustiadi, E.; Barus, B.; Pravitasari, A.E. Systematic Literature Review: Research Development of Urban Resilience in Metropolitan Areas. Sustainability 2025, 17, 7380. https://doi.org/10.3390/su17167380
Saptono Y, Rustiadi E, Barus B, Pravitasari AE. Systematic Literature Review: Research Development of Urban Resilience in Metropolitan Areas. Sustainability. 2025; 17(16):7380. https://doi.org/10.3390/su17167380
Chicago/Turabian StyleSaptono, Yudi, Ernan Rustiadi, Baba Barus, and Andrea Emma Pravitasari. 2025. "Systematic Literature Review: Research Development of Urban Resilience in Metropolitan Areas" Sustainability 17, no. 16: 7380. https://doi.org/10.3390/su17167380
APA StyleSaptono, Y., Rustiadi, E., Barus, B., & Pravitasari, A. E. (2025). Systematic Literature Review: Research Development of Urban Resilience in Metropolitan Areas. Sustainability, 17(16), 7380. https://doi.org/10.3390/su17167380