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Review

Systematic Literature Review: Research Development of Urban Resilience in Metropolitan Areas

by
Yudi Saptono
1,*,
Ernan Rustiadi
2,3,
Baba Barus
3,4 and
Andrea Emma Pravitasari
2,3
1
Regional and Rural Development Planning Science Study Program, Faculty of Economics and Management, IPB University, Bogor 16680, Indonesia
2
Regional Development Planning Division, Department of Soil Science and Land Resources, Faculty of Agriculture, IPB University, Bogor 16680, Indonesia
3
Center for Regional System Analysis, Planning and Development (CRESTPENT), IPB University, Bogor 16680, Indonesia
4
Remote Sensing and Spatial Information Division, Department of Soil Science and Land Resources, Faculty of Agriculture, IPB University, Bogor 16680, Indonesia
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(16), 7380; https://doi.org/10.3390/su17167380
Submission received: 17 June 2025 / Revised: 8 August 2025 / Accepted: 11 August 2025 / Published: 15 August 2025
(This article belongs to the Topic Disaster Risk Management and Resilience)

Abstract

Metropolitan areas worldwide are facing growing pressures, such as high population density, environmental degradation, and socio–economic challenges. Urban resilience has become a key focus in addressing these issues. This study explores the development of urban resilience research in metropolitan areas through a systematic review using the PRISMA method of SCOPUS-indexed articles. The review shows a significant annual increase in urban resilience studies, with three main themes clustered into environment, urban planning, and social–human dimensions. Highly cited research emphasizes urban concepts, resilience measurement of urban systems against various shocks, and resilience dimensions. Notably, metropolitan areas in Asia lead in urban resilience-related discussions, particularly in response to frequent and diverse shocks. Most studies apply quantitative methods at the city/metropolitan scale, using multi-dimensional resilience indicators. The literature highlights the distinct characteristics of Asian metropolitan regions compared to others, underlining the need to assess resilience not only in urban cores but also in peri-urban, desakota, and rural settings. These findings stress the importance of formulating policies that promote adaptive, sustainable and local ecosystem management to strengthen urban resilience across different metropolitan landscapes.

1. Introduction

Research shows that by 2050, approximately two-thirds of the world’s population will live in urban areas, marking a significant shift from rural to urban living [1,2]. Rapid urbanization poses challenges to mental health and well-being, especially in developing countries that often lack adequate support services [1]. The accelerating pace of urbanization and the expansion of urban areas beyond administrative boundaries [3] has also exposed the fragile ecological future of cities, which are engines of innovation and economic growth [2]. Cities are places that people depend on to live, but on the other hand, many social, economic and environmental problems challenge the survival of people living in these areas.
Currently, cities worldwide are experiencing significant pressure in all aspects. This ranges from increasing urban population density, environmental degradation, and social pressures to the economic challenges increasingly felt by urban communities today. Various studies have been conducted regarding the challenges faced by cities, one of which is the extent to which they can withstand shocks, known as urban resilience. In contrast to urban sustainability, which focuses on long-term viability, balancing environmental, social, and economic aspects, urban resilience emphasizes the ability to withstand and recover from specific disturbances/shocks [4] that occur suddenly and in a short period of time [5]. Although different in purpose, both are equally important in the rational development planning process so that cities can be resilient and sustainable [6]. The concept of urban sustainability is already well established compared to urban resilience, which has only developed in recent years, in response to numerous shocks. Therefore, through a review of the literature related to the development of the concept of urban resilience, especially in metropolitan areas, in-depth and comprehensive rational urban planning can better address the problem of urban uncertainty from various pressures through urban resilience principles without abandoning urban sustainability principles in the future.
When discussing cities, we inevitably consider their development to form urban areas, known as metropolitan areas. The concept of metropolitan areas has been extensively explored by researchers, defining their function or role not only in terms of socio–economic centers but also in terms of the interconnectedness of surrounding areas. According to [7], the definition of “metropolitan” emphasizes the functional and spatial integration of urban areas. In his work, Bourne defines a metropolitan area as “An integrated economic and social unit with a core urban center and surrounding communities that are linked by employment, commuting patterns, and social and service networks.”
Bourne’s definition indicates that there are three key elements of metropolitan areas:
  • 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).
Bourne’s perspective laid the groundwork for understanding metropolitan areas not only in terms of population density or size, but more importantly, in terms of interaction and interdependence across urban and suburban spaces. Likewise, [8] explained that a metropolitan area is the spatial spread of core cities outside their city limits, which creates a large urban agglomeration. These metropolitan areas typically include satellite cities, small towns, and rural areas that are socioeconomically tied to the main cities or urban cores and are often measured by travel patterns, employment linkages, and public services.
The definition of resilience itself comes from the Latin word “resilio” which means “return to its original state” [9,10,11]. Originating in the field of ecology in the 1970s, ‘resilience’ is understood as the capacity of a system or agent to maintain or restore functionality in the event of disturbance or stress [12]. Thus, urban resilience refers to the ability of cities to adapt, recover, and rebuild quickly in the face of various stresses, shocks, and disasters [13,14].
Meanwhile, according to [15], resilience is defined as the capacity of individuals, communities, and systems to survive, adapt, and grow in the face of stress and shocks, and even transform when conditions require it. In line with this, the [16] describes resilience as the capacity of a community or society system that has the potential to be exposed to disasters to adapt, by surviving or changing in such a way as to achieve and maintain an acceptable level of function and structure. This is determined by the level of ability of the social system to organize itself to increase its capacity to learn from past disasters, better protect itself in the future, and improve disaster risk reduction efforts.
Resilience is generally seen as a broader concept than capacity because it goes beyond the specific behaviors, strategies, and actions for risk reduction and management that are typically understood as capacity. However, it is difficult to clearly distinguish between these concepts. Ref. [17] explains that in everyday usage, “capacity” and “coping capacity” are often used interchangeably with “resilience.” He further explained that resilience encompasses three meanings:
  • 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.
The definition of resilience has been refined to include the ability to withstand and overcome disasters with minimal impact and damage [18]. It includes the capacity to reduce or avoid damage, contain the impact of disasters, and recover with minimal social disruption [18]. Resilience in “hazard” research generally focuses on engineering and social systems, and includes pre-disaster actions to prevent the occurrence of hazards, damage and losses (preparedness) and post-disaster strategies to help cope with and minimize the impact of disasters [18].
In this context, metropolitan cities that are geographically and geologically located in disaster-prone locations with varying urban system capacity capabilities make it important to review the concept of urban resilience in more depth.
Although experts have found that urban resilience is dynamic, complex, multifaceted, multidimensional, and multifactorial, the concept of urban resilience has been widely discussed and developed in a clear and coherent manner [5]. The concept of resilience, including the determination of resilience dimension categories, shock types and spatial scales of urban resilience assessment, has been clearly structured, as summarized in Table 1, Table 2 and Table 3.
However, to build such complex resilience in the future, it is necessary to build an integrated framework and tools [24] for urban governance, planning, and policy formulation in building adaptive and sustainable cities [25]. Therefore, through this literature review, the development of urban resilience research in metropolitan areas will be identified by examining the types of shocks that occur, the research methodology used, the spatial scale of the research object, and the indicators used, so that the existing research gap can be identified with the aim of building a more integrated urban resilience framework. Through this systematic literature review (SLR), at least three questions were asked to explore the extent to which research related to this topic has developed:
  • 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

Using the PRISMA method—Preferred Reporting Items of Systematic Re-views and Meta-Analysis—as a reporting guideline or manual to improve transparency and quality of reporting in systematic reviews and meta-analyses [26], the author compiled answers to the three questions above. The article database was used to review international articles, either in the form of papers/journals or book chapters, indexed by SCOPUS, with a retrieval deadline of 24 January 2025. The SLR stages are as follows:
  • 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.
The article search flow is illustrated in Figure 1.
The initial stage of the article review was to determine the relevance of keywords from articles identified based on the keywords mentioned above. Using VOSviewer application version 1.6.20, the number of occurrences and strength of the links between keywords (links) can be seen by forming several clusters of associations. More occurrences of keywords indicated that more people were conducting research on the topic of this keyword, which was related to other keywords, and the strength of links showed which keywords act as a ‘bridge’ between conceptual clusters.
In addition, it is also seen which topics have novelty from the relevance of the keywords, as indicated by the change in gradation from blue to yellow. The more yellow the circle color of each keyword, the more the topic related to the keyword is still relatively new to be discussed; conversely, the bluer the circle color, the longer the topic of the keyword has been discussed.
In the next stage, based on the 248 articles reviewed, the author maps which metropolitan areas are widely discussed based on the grouping of the types of disasters/shocks [5] that arise and correspond to the continent in which the metropolitan area is located. The division of continents is grouped into six parts: metropolitan Asia, metropolitan Europe, metropolitan North America, metropolitan South America, metropolitan Africa, metropolitan Australia, and New Zealand. Each metropolitan area on each continent has different characteristics in terms of geography, climate, demographics, sociocultural factors, and other factors that affect the resilience of the metropolitan area in that location.

3. Results

3.1. Keyword Correlations on Urban Resilience in Metropolitan Areas

Based on the database with the theme of urban resilience in metropolitan areas or megacities, the relationship between keywords taken from the top 100 three clusters formed by looking at the frequency of occurrences (Figure 2), the frequency of links and the strength of the links between keywords (Figure 3).
Figure 2 shows the number of keywords that appeared in each cluster. Cluster 1 (red color) is a cluster of 36 different keyword terms centered on the word “China” (77 occurrences). This word has the highest frequency in Cluster 1; other high-frequency words (26 occurrences) in Cluster 1 included land use, green infrastructure, ecosystem services, ecosystem resilience, and GIS. For medium-frequency occurrences (16–24 occurrences), the terms urban ecosystem, urban sustainability, remote sensing, biodiversity, spatiotemporal analysis, urban agriculture, and urban policy were used. For low frequency (less than 16 occurrences), there is accessibility, connectivity, infrastructure plan, rapid urbanization, urban forestry, and coastal zones to land use change.
In Cluster 2 (green), from 32 different keywords, the term “metropolitan area” is seen as the word that has the most occurrences of all clusters (206 occurrences) and has a strong relationship between words in the cluster and between clusters. Other high-frequency keywords with more than 50 occurrences are resilience, urban planning, climate change, urbanization, sustainable development, urban resilience, megacity, sustainability, the United States, and urban development. Keywords with a medium frequency of occurrence and relationships between keywords in the cluster and between other clusters include the following: risk assessment, urban growth, vulnerability, governance approach, adaptive management, decision making, flooding, megacities, green space, disaster management, spatial planning, and strategic approach. Meanwhile, keywords that had a low frequency in Cluster 2 were flood control, water management, water supply, extreme event, heat island, and mitigation.
Furthermore, for Cluster 3 (blue) with 32 keywords, the term “urban area” is the most frequently occurring keyword (98 occurrences) and has a strong relationship with the other two clusters. Other keywords that have a high frequency of occurrence include human, COVID-19, urban population, and city. Keywords with medium frequency were cities, neighborhoods, spatial analysis, controlled study, and urban. Meanwhile, keywords with a low occurrence but still having a relationship with keywords in the same cluster and other clusters are disaster, adult, environmental protection, quality of life, risk management, male, perception, public space, risk factor, building, adolescent, majority clinical study, middle-aged, and semi-structured interview.
Figure 3 shows the frequency and strength of the links among the keywords from 100 keywords selected as bridges/connections between clusters. In Cluster 1 (red), six keywords have the largest links among keywords and the strength of links among keywords, including the keyword “China,” which has 99 links with other keywords in all clusters, with a strength of links among keywords of 574. The next keywords were “land use” (link: 98, strength of link: 373), “ecosystem services” (link: 93, strength of total link: 339), “ecosystem resilience” (link: 93, strength of total link: 312), “GIS” (link: 93, strength of total link: 239) and “spatiotemporal analysis” (link: 94, strength of total link: 217).
In Cluster 2 (green), six keywords that have the greatest links among keywords and the strength of the links among keywords: “Metropolitan Area“ (link: 99, strength of link: 1072), “urban planning” (link: 98, strength of link: 720), “urbanization” (link: 99, strength of total link: 631), ”climate change” (link: 98, strength of total link: 614), “resilience” (link: 98, strength of total link: 597) and “sustainable development” (link: 99, strength of total link: 496).
Cluster 3 (blue) has six keywords with the largest number of links among keywords and the strength of their keywords, namely: “urban area” (link: 99, strength of link: 701), “human” (link: 97, strength of link: 468), “controlled study” (link: 94, strength of link: 236), “spatial analysis” (link: 94, strength of link: 200) “urban population” (link: 90, strength of link: 242) and “COVID 19” (link: 88, strength of link: 189).
Based on the occurrence and link results of the keyword associations above, it can be concluded that Cluster 1 (red) keyword associations discuss “environmental issues” more, with keywords that function as a bridge among clusters, namely, “China, land use, ecosystem services, ecosystem resilience, GIS and spatiotemporal analysis”. Cluster 2 (green) discusses “urban planning” more, with the main keywords connecting clusters being “metropolitan area, urban planning, urbanization, climate change, resilience and sustainable development”. Cluster 3 (blue) discusses “social and human issues” more with the main keywords connecting clusters “urban area, human, controlled study, spatial analysis, urban population and COVID 19”.
Figure 4a–d illustrate the correlation between countries that publish the most articles on urban resilience in metropolitan areas, as well as the latest developments in research on this topic. Figure 4a shows the relationships between “country” nodes, indicating the number of documents published by those countries. The lines connecting the nodes represent collaboration between countries. The color of the nodes and lines indicates the year of the research. Larger nodes represent a higher number of published documents, and the more yellow the node and line colors, the more recent the research. The United States (222 documents), China (202 documents), Italy (133 documents), the United Kingdom (83 documents), India (69 documents), and Germany (52 documents) rank as the countries with the most publications on urban resilience in metropolitan areas. Meanwhile, recent research topics are mostly discussed by authors from China. Looking at the continental distribution, many Asian countries with metropolitan areas also contribute significantly to this topic, including China, India, Japan, South Korea, Indonesia, Taiwan, Hong Kong, Thailand, Nepal, Iran, and Pakistan. This reflects the high frequency of disasters or shocks occurring in metropolitan areas across Asia.
The United States, China, and Italy are the three countries with the highest number of publications on this topic. The United States began research on this topic in 2003, earlier than China and Italy (Figure 4b). The initial keywords that emerged until 2017 were ‘neighborhood,’ ‘urban system,’ ‘governance approach,’ and ‘green space.’ Research developments began to focus more on ‘resilience’, ‘vulnerability’, ‘urban planning’ and ‘disaster management’ during 2018–2020, while by 2022, studies had progressed to include keywords such as ‘human,’ ‘urban climate,’ and ‘environmental justice’.
China is the second-highest country in terms of the number of published documents on this topic. Research began in 2014 with initial keywords that emerged until 2022, such as ‘resilience,’ ‘flooding,’ and ‘megacity.’ The research progressed in 2023, focusing on keywords such as ‘urban area,’ ‘metropolitan area,’ ‘ecosystem resiliency,’ and ‘urbanization.’ By 2024, the latest studies explored keywords such as ‘environmental protection,’ ‘conservation of natural resources,’ non-human, ‘abiotic‘ and ‘ecosystem services.’
The third country is Italy. As a European nation, Italy began its research on this topic in 2015, with the initial keywords being ‘decision making’ and ‘biodiversity’. In the following year, 2021, the focus shifted to topics such as ‘urban growth’, ‘urbanization’, ‘resilience,’ and ‘metropolitan area.’ The research continued to develop in 2022, with increasing attention to ‘climate change,’ ‘urban regeneration,’ and ‘infrastructure.’
From the research developments on urban resilience in metropolitan areas across these three countries, it can be seen that the current research trend is increasingly directed toward environmental issues, human aspects, and climate change. Among the three, China continues to be the most active in conducting research on this topic.

3.2. The Development of Urban Resilience Research Topics in Metropolitan Areas in the World from Year to Year

The search results for articles that underwent the SLR process can be seen in the development of urban resilience research topics in metropolitan areas. Figure 5 shows that the number of articles related to the topic of urban resilience in metropolitan areas has started to grow rapidly in the past 15 years or since 2010, whereas before 2010, research related to this topic had not developed much.
When viewed from the types of shocks that occurred in several review periods, it can also be seen that the shocks were increasingly diverse in nature. In the period before 2010, the discussion of resilience was limited to natural disasters and social aspects, while in the following 10-year period, the issue of resilience began to develop into the issue of climate change, energy crisis, and increasingly in the current period, pandemics and technological disruption. This trend highlights the increasing importance of studying the vulnerabilities of metropolitan areas each year, in response to various shocks, whether natural, man-made, or non-natural.
The research topics that are widely cited to provide an overview of the trend issues being widely discussed on this topic (Table 4) include the 12 city categories (sustainable city; ‘green city’; ‘digital city’; ‘smart city’; ‘intelligent city’; ‘information city’; ‘knowledge city’; ‘resilient city’; ‘eco-friendly city’; ‘low carbon city’; ‘livable city’) written by [27]. The various city concepts explained provide learning opportunities for researchers to use these terms, at least if they want to understand their implications for urban development and regeneration policies and practices. The concept of urban resilience itself is explained in several other journals that have the most citations, including research conducted by [28], who views the city from a resilience perspective, which can encourage better integration of ecological and social considerations in urban planning, resulting in a more adaptive and sustainable urban environment. In addition, the city resilience analysis model was explained by [29], who showed the effectiveness of various resilience strategies through dynamic system simulations. The differences in overcoming resilience between villages and cities are also interesting and widely cited. Ref. [30] explained that there are significant differences in disaster resilience between urban and rural areas. Resilience in urban areas is mainly driven by economic capital, whereas community capital is the most important driver of disaster resilience in rural areas.
Other urban resilience topics that are widely cited are how urban systems are measured for their resilience to shocks, such as urban farming systems supporting food security during the COVID-19 pandemic [31], measuring resilience in metropolitan railway networks [32], slum development in disaster recovery [33], and special discussions on the use of roofing material colors that can reduce the impact of urban warming [34]. Topics on urban resilience that review the dimensions or types of shocks that occur are also widely cited, such as measuring resilience due to flooding by [35] through modeling and spatially by measuring a spatial urban flood resilience index. Another study by [36] compared flood risks in metropolitan city systems using the analytical hierarchy process (AHP) and interval AHP (I-AHP) methods. The impact of climate change and global warming has also been a widely cited topic in recent years, including how the level of vulnerability to temperature warming differs between urban centers and the outskirts of urban areas. The recommendations from this study are based on mitigation and adaptive strategies, such as environmentally friendly actions and the existence of a health database, in an effort to increase climate resilience [37].
The topic of urban resilience is also widely cited by examining the dimensions of resilience, such as the economic dimension in the research of [38] related to circular economic resilience in waste management. The ecological dimension is related to the assessment of ecological risks of urban landscapes through the adaptive cycle framework of [39], changes in ecological resilience in metropolitan areas and the implications of resilience management to improve adaptation and sustainable development in coastal urban areas from the research of [40].
Table 4. Top 20 urban resilience research article titles in metropolitan areas with the highest number of citations per year.
Table 4. Top 20 urban resilience research article titles in metropolitan areas with the highest number of citations per year.
The Number of Citations in ScopusTitleAuthorsNumber of Quotes per Year
1Sustainable-smart-resilient-low carbon-eco-knowledge cities; Making sense of a multitude of concepts promoting sustainable urbanization[27]7950
2Urban flood resilience. A multi-criteria index to integrate flood resilience into urban planning[35]6167
3Home gardening and urban agriculture for advancing food and nutritional security in response to the COVID-19 pandemic[31]5920
4Flood risk assessment in metro systems of mega-cities using a GIS-based modelling approach[36]4886
5Resiliency assessment of urban rail transit networks: Shanghai metro as an example[32]2743
6Resilient cities: Meaning, models, and metaphor for integrating the ecological, socio–economic, and planning realms[28]2700
7Urban—Rural Differences in Disaster Resilience[30]2467
8System dynamics modelling for improving urban resilience in Beijing, China[29]2280
9Green and cool roofs to mitigate urban heat island effects in the Chicago metropolitan area: Evaluation with a regional climate model[34]2244
10Evicting slums, ‘building back better’: Resiliency revanchism and disaster risk management in Manila[33]1783
11Heat vulnerability caused by physical and social conditions in a mountainous megacity of Chongqing, China[37]1733
12Exploring the spatial–temporal dynamics of ecosystem health: A study on a rapidly urbanizing metropolitan area of Lower Gangetic Plain, India[41]1725
13Spatial–temporal variation, driving mechanism and management zoning of ecological resilience based on RSEI in a coastal metropolitan area[40]1600
14Steps toward a resilient circular economy in India[38]1575
15Adaptation responses to climate change differ between global megacities[42]1567
16Analyzing the level of accessibility of public urban green spaces to different socially vulnerable groups of people[43]1557
17Assessing urban landscape ecological risk through an adaptive cycle framework[39]1529
18Modelling pedestrian emotion in high-density cities using visual exposure and machine learning: Tracking real-time physiology and psychology in Hong Kong[44]1250
19From the smart city to the smart metropolis? Building resilience in the urban periphery[45]1167
20Equality of access and resilience in urban population-facility networks[46]1067
Table 5 illustrates the relationship between the type of shock and the geographic location of metropolitan areas. Environmental shocks, particularly natural disasters, are the most frequently reported, followed by economic, human-induced, and technological shocks. Additionally, when examining the regions where these disasters are most commonly studied in the context of urban resilience, Asia stands out as the most frequently analyzed. This suggests that metropolitan areas across Asia, especially in East Asia (e.g., China, Japan, South Korea) and Southeast Asia (e.g., Thailand, the Philippines, Indonesia) face significant challenges related to regional vulnerability and exposure to various types of shocks and disasters.

3.3. Identification of Spatial Scales, Research Methods, and Indicators for Urban Resilience Assessment in Metropolitan Areas

Based on the results of the identification of the reviewed articles, the author attempted to analyze how many articles discussed urban resilience in metropolitan areas based on the spatial scale of the area, whether they discussed community/society scale, local scale (district or subdistrict), city scale, or regional or national scale (Figure 6a). The results of the search showed that almost 70 percent of these articles discussed the city scale. Metropolitan areas, although they cross urban administrative boundaries or borders between regional areas, are considered because of the ease of available data and the level of complexity. According to [47], the greater the spatial level, the more factors that play a role and increase the complexity of the system. Thus, the greater the spatial scale, the more factors that influence the complex system, and the easier it is to understand the selection of urban area scales.
The research approach is shown in Figure 6b. More than 50% of the reviewed articles used a quantitative approach, 31% used a qualitative approach, and the rest used a mixture of quantitative and qualitative methods. This shows that the quantitative approach method is used to evaluate whether the area is resilient through various evaluations, such as those related to the type of shock, dimensional form, measurement of indicators, spatial relationships, and other evaluation approaches.
Various analyses are conducted for each research method approach. Table 6 shows, based on the results of the SLR, the types of analyses used by the authors for each methodological approach (quantitative, qualitative, and mixed methods) in measuring urban resilience in metropolitan areas. The choice of analysis is also adjusted according to the spatial scale at which the research is conducted.
The final discussion in this SLR is to trace the indicators used by researchers in measuring or evaluating urban resilience in metropolitan areas, which can be a reference for researchers in building an operational index to measure resilience at the study location. Identification is carried out by grouping based on the dimensions of resilience (social, economic, ecological, physical and institutional), spatial scale, type of shock and analysis used. The results of the indicator search are diverse, with various analyses adjusted for the type of shock (Appendix A). Generally, the selection of indicators for measuring the level of urban resilience can be determined by which resilience dimension is measured. In the social dimension, the selection of indicators is more directed at the ability of cities, groups or communities to overcome disruptions due to social changes, such as education, employment, health, population and political conditions. In the economic dimension, the selection of indicators is directed at the ability to independently regulate the economy, both the structure and socio–economic system, toward economic balance by looking at the level of income and fiscal management of the government, employment, trade, economic development, innovation and industry, population savings and investment development. In the infrastructure dimension, indicators are widely used to measure the quality of infrastructure and the ecosystems within it, such as transportation, communication, energy and settlement facilities (drinking water, sanitation, drainage), all of which aim to provide, protect and connect communities in the region. Finally, the selection of indicators in the institutional dimension is directed to assess the ability of all types of institutions and actors within them, such as service level, participation level, governance, skill level, and local content, in adapting to changes due to shocks.

4. Discussion

4.1. Urban Resilience Research Trends in Metropolitan Areas

4.1.1. Review: Correlation Between Keywords

Research trends on urban resilience in metropolitan/megacity areas, based on keyword correlations, revealed three clusters, each with the keywords of environment, urban planning, and human and social issues. The first cluster keyword, “environment,” indicates a link between environmental factors and urban resilience. Several studies have found that intensive and efficient land use (the primary keyword of the environmental cluster) in metropolitan China significantly impacts urban resilience [77,78]. Similarly, when combined with other key keywords from other environmental clusters, such as ecosystem services, several studies have shown a strong link with urban resilience [79,80]. This suggests that environmental management has a strong relationship with urban resilience.
The second cluster keyword, “urban planning,” is also a keyword related to urban resilience. Several studies have highlighted the importance of integrating urban resilience principles into multi-scale planning policies in metropolitan areas [81] through the concepts of vulnerability, adaptive capacity, and governance [82]. Ref. [6] highlights that rational urban development can be achieved if cities are resilient and sustainable. Therefore, urban planners, policymakers, and researchers must consider the key issue of urban resilience in rational urban planning.
The third cluster keyword is “social and human,” emphasizing that the community is no longer viewed merely as an object but as an active participant in shaping urban resilience. Multiple studies highlight the significant role of social connectedness in enhancing urban resilience [83,84].
From these three clusters, it can be concluded that the level of urban resilience is related to how the environment of a region is managed and planned and the interaction/connectedness between the people living in that region.
Research trends related to this topic can also be observed by analyzing the differences in the development of research topics in the three countries with the highest number of publications (the United States, China, and Italy). The analysis is conducted by examining the background and policies adopted in each country, focusing on the interrelation of keywords across different time periods.
The early development of research in the United States up to 2017 was represented by the keyword “neighborhood,” which highlights the importance of local context in the participatory process of adaptive planning for climate change [85], as well as the significance of social networks in determining the capacity of cities and suburbs to cope with shocks or disruptions [86]. After 2017, research on urban resilience gradually increased, with a more noticeable growth trend during the 2018–2019 period. During this time, due to the negative impacts of urbanization and natural disasters, such as flooding, the U.S. began to place more emphasis on disaster management. Climate change became a major topic from 2022 to the present. During this period, addressing extreme heat has become a key aspect of climate adaptation planning [87,88]. Context-specific policy analyses and coordinated efforts among agencies are crucial for developing targeted interventions to reduce heat-related illnesses and fatalities [89].
The development of resilience in China began with the keyword “flooding,” as this type of disaster has been a major concern in the country. Research shows that urban resilience efforts must target vulnerable poor populations affected by flooding [90] and should be carried out through a systematic and dynamic approach, particularly for the protection of coastal areas [91]. Alongside this, continuous industrialization and rapid urbanization have driven the fast growth of Chinese cities. However, the negative impact of this development, such as resource shortages, environmental degradation, and land use conversion, poses significant threats to the country. To address the challenges of urbanization and climate change, China has implemented ecosystem-based adaptation strategies, such as the Sponge City initiative [92]. This approach aims to enhance urban water resilience and sustainability by integrating ecosystem-based solutions into urban planning [93]. Recently, multi-dimensional evaluations have shown that environmental and institutional resilience in China tends to be relatively high, while economic, social, and infrastructure resilience lag behind [94].
Italy began the development of urban resilience research in metropolitan areas with a focus on environmental issues, particularly in the keyword “biodiversity.” This indicates that Italy showed considerable concern for environmental preservation in the early stages of research development, including the implementation of greening programs prioritized based on ecological and social criteria [95]. Similar to the United States and China, the development of resilience and sustainability topics in Italy has grown alongside urbanization and urban growth in its cities. Climate change has also become a widely discussed topic in recent years in Italy. Urban resilience and climate change adaptation are becoming increasingly important for Italy’s metropolitan areas. Research highlights the need for integrated approaches, such as multi-criteria decision making for vulnerability assessments [96], and emphasizes the importance of science–policy–practice dialogue, which is still lacking in many Italian metropolitan cities when addressing climate change [97].
The correlation between keywords and research developments in the three countries with the highest number of publications shows that “human” and “environment” are the main keywords in adapting to various stresses and shocks occurring in metropolitan areas.

4.1.2. Review: Highly Cited Research

Several studies related to urban resilience in metropolitan areas that are widely cited as SLR results show several things that can strengthen the concept of urban resilience in metropolitan areas. The terminology of urban concepts mentioned by [27], such as “smart city” or “resilient city,” demonstrates that these concepts are not merely jargon but have major implications for policy approaches and development strategies. This relates to the explanation of the correlation between the keywords “urban planning” and “urban resilience,” which requires the integration of both. A review of the characteristics of urban resilience shows that urban resilience is multidimensional, not only related to physical infrastructure but also the social and ecological systems that support urban life [28]. Furthermore, urban resilience is also multi-sectoral. Several studies have been conducted on specific shocks in each sector, such as food security and urban agriculture during the pandemic [31], urban railway networks [32], post-disaster slum planning [33], and roof color for urban temperature mitigation [34].
Another important aspect is the widely cited research by [30] regarding the differences between urban and rural resilience. They explain that resilience policies cannot be generalized but must be tailored to the local characteristics and socio–economic structure of each region. This is because each region has different system capacities, with urban areas having a stronger economic structure than rural areas, while rural areas possess a greater social capital system capacity. Therefore, it is crucial to review local characteristics and socio–economic structures in determining resilience policies.

4.1.3. Review: The Types of Shocks That Occurred

Based on the results of the analysis of the development of urban resilience research topics, where the author divided it into three research year periods, it can be seen that the trend of research development increases from year to year when viewed from the cases of the shocks that occur.
At the beginning of the review period, before 2010, the research trend was more toward how cities can cope with shocks from social pressures, environmental degradation and natural disasters. In several studies during this period, the concept of urban resilience began to emerge, leading to urban planning through an integrated social and ecological system [28]. This is reinforced by [86]’s argument that the urban ability to face crises depends on the strength and connectivity of its environmental and social network, which is further strengthened by social and economic integration and relations with the political system. This clarifies that the relationship between the environment and human society is a key factor in urban resilience.
In the next 10 years, the impacts of global climate change and the energy crisis will begin to emerge. In addressing climate change, research shows that the interplay between resilience, vulnerability, and adaptation is crucial for understanding long-term changes in urban spaces and managing climate-related disaster risks [98]. Moreover, investments in infrastructure and public facilities may provide short-term benefits but potentially lead to maladaptive outcomes in the long term, highlighting the need for more effective adaptive policies in metropolitan governance [98]. This shows that urban resilience is an integrated system that involves not only one dimension but multiple dimensions. Another emerging shock issue in this period is the energy crisis, where a sustainable energy transition is necessary to address the threat of this crisis. One notable aspect of the policy response to the energy crisis in metropolitan Europe is the rise of energy communities, which are becoming key players in the urban energy transition and contribute significantly to sustainability and resilience. These communities enable the collective generation, distribution, and consumption of renewable energy, promoting self-consumption and collaboration [99,100,101]. This shows that the community as part of the human social keyword, plays an important role in urban resilience when a crisis occurs.
From 2020 to the present, shocks due to natural disasters and disease transmission, such as the COVID-19 pandemic from 2020 to 2021, have also become a widely discussed issue. Based on a few studies, to enhance resilience against future pandemics, cities must focus on various aspects, including the economy, environmental management, governance, social inequality, smart city solutions, transportation, and urban design [102]. Key strategies involve pre-event planning, long-term visioning, early response, integrated governance, community empowerment, and the appropriate use of technology [102]. Again, learning from this pandemic shock, the keywords of urban planning and social human representation for communities play an important role in urban resilience. Apart from that, technological disruption in the transformation of urban systems is also a new issue that emerged during this period. As a continuation of the impact of COVID-19, it has also affected how urban systems transform into community activities during the pandemic, which has resulted in many restrictions on activities. From research we know that cities with diverse, flexible, and adaptable technological knowledge bases tend to be more resilient to crises and recover quickly from disruptions [103]. Cities that are adaptive to changes in their urban systems are key to overcoming the shock caused by today’s disruptive technology.

4.2. Urban Resilience in Metropolitan Asia and Resilience Research Challenge

Why are metropolitan areas in Asia becoming areas that are quite widely discussed regarding urban resilience as a result of the SLR above, and how do these special characteristics affect urban resilience in these metropolitan areas in the face of various shocks that occur? From a geographical perspective, metropolitan areas in Asia are mostly located in the Pacific Ring of Fire. Many Asian countries, such as Japan, Indonesia, and the Philippines, are located in this tectonically active region, making them prone to earthquakes and volcanic eruptions. In addition, many large cities in Asia, such as Jakarta, Bangkok and Manila, are starting to develop in areas around deltas and coastal areas [104], because they are located in a monsoon climate region with high rainfall, making them very vulnerable to flooding, tropical storms (typhoons), and rising sea levels. Climate change has also increased the vulnerability of metropolitan areas in Asia. Increasing global temperatures cause extreme weather, flash floods, droughts, and heat waves, which are increasingly frequent and intense.
Demographic factors also affect urban vulnerability in metropolitan areas. Along with urbanization and suburbanization, Asian cities are experiencing large population growth compared to other cities in the world [105]. However, the fastest urbanization occurs in Asia, and unfortunately, most of it in the form of growing metropolitan cities or megacities, which causes complex problems. Metropolitan cities, such as Tokyo, Mumbai, Jakarta, and Dhaka, have populations of millions in dense spaces, causing new problems, such as the emergence of slums in disaster-prone areas, so that small disasters can have a major impact on humans and assets.
An interesting part of metropolitan areas in Asia that needs to be reviewed is the fringe region known as peri-urban, rural and urban areas [106]. In contrast to the process of urbanization and suburbanization in metropolitan areas of the United States and Europe which extend to less densely populated rural areas, studies of metropolitan areas in Asian countries show that the expansion of metropolitan areas is spreading to densely populated rural areas, so that the outward expansion of the largest metropolitan areas has eroded the long-standing distinction between rural and urban [106]. However, the results of the measurement of rural and urban climate resilience in the Yangon Metropolitan area show that resilience in this area is a continuous and uneven process across the urban–rural spectrum influenced by factors such as land use, community structure and urbanization patterns [107].
Given the various factors mentioned above, it is relevant that research related to resilience in metropolitan areas of Asia is widely studied. Therefore, it is important for Asian cities to develop risk-based planning systems, build adaptive infrastructure, and empower local communities to respond to the shocks.
Based on the SLR results, research related to the resilience of Asia metropolitan is a focus that needs to be studied more deeply, considering the characteristics of this area, which are different from metropolitan areas in other continents, where the characteristics can no longer be distinguished between rural and urban areas. Thus, areas, especially the outskirts of metropolitan areas in Asia (peri-urban, desakota, rural areas) become important to study further. This is reinforced by several arguments from researchers, such as [8], who stated that policies for peri-urban areas, such as desakota, must be carried out carefully and focus more on the sustainability and livability of this area. In addition, because the desakota zone may be vulnerable to international economic fluctuations, which can result in unemployment and increased poverty, the development of governance and management in this metropolitan area is important. Likewise, [108] explains the existence of the term desakota in the Asian metropolitan area created as an effort to focus on intense interaction and resilience of rural and urban activities.
The explanation above shows that urban resilience research at the local scale needs to be reviewed more deeply in the future in this region. This suburban area is likely to have a lower level of resilience than other metropolitan areas. A review on a smaller scale (local/community/individual scale) is expected to reveal more comprehensive urban problems and recommendations, especially for urban spatial planning policies in metropolitan areas that are more adaptive and sustainable. Likewise, for the approach method, a mixed method combining quantitative and qualitative approaches, examining the performance and capacity of the urban system comprehensively in the fringe area, becomes the main analysis method for assessing the level of resilience in this region.

4.3. Selection of Research Methods, Spatial Scales and Indicators in Measuring Urban Resilience

The SLR results show that many researchers have used quantitative approaches to measure the level of resilience of a region compared to qualitative or mixed methods. Each of these approaches has advantages and disadvantages, which can be explained as follows.
Urban resilience can be easily identified through one approach, namely, looking at changes in the city system, both in terms of function and city structure [15]. Systems within a city usually provide similar services, such as providing food and water for citizens, supplying electricity and other utilities, facilitating trade in goods and services, and creating and enforcing laws, among others. Changes in these systems will be seen from two forms of resilience: resilience in terms of performance and capacity of a city system [5]. This performance assessment evaluates or assesses the response of an area to shocks (i.e., whether the city is resistant, resilient or non-resilient), whereas the capacity assessment examines the underlying adaptive capacity of the urban system in responding to shocks (i.e., short-term and sudden disturbances) [5].
According to [5], the research methodology for measuring urban resilience is divided into two approaches: a deterministic approach that examines the performance of urban systems, which is generally a quantitative analysis, and a heuristic approach that measures the adaptive capacity of urban systems, which is usually a qualitative analysis. Each approach has advantages and disadvantages. The deterministic approach has the advantage of being able to explain whether the area is resilient, why it is resilient and the form and determining factors of resilience. However, one disadvantage of this approach is that it cannot clearly explain the type of resilience that occurs. While the heuristic approach can clearly interpret the type of resilience (such as engineering, ecology, evolutionary and transformational), it cannot determine whether the area is resilient. In addition, the heuristic approach has weaknesses because it relies on the amount of data available, practical rules, everyday experience, and logical thinking, rather than following systematic procedures, such as the deterministic approach, so that errors or suboptimal decisions in some cases also occur. As a result, several economic geographers propose integrating comparative case studies with quantitative analysis to improve the assessment of resilience [24]. They emphasize that qualitative methods play a crucial role in uncovering the specific mechanisms driving urban resilience, which often remain hidden when relying solely on quantitative approaches. Therefore, a fairly comprehensive approach to measuring urban resilience is a mixed-method approach that combines the strengths of both deterministic (quantitative) and heuristic (qualitative) approaches to propose a synthesis framework applicable in future studies. Thus, that research can answer whether it is resilient, why vulnerability or resilience occurs and how it occurs. In Table 6, it can be concluded that the various analysis used in the qualitative method explains how the adaptive capacity of the urban system responds during a shock/disruption. While the various analyses in the quantitative method describe the performance of the urban system as it is affected by the shock. A mixed-method analysis, which combines both qualitative and quantitative approaches, can explain both aspects. It shows how adaptive the area is and how well it performs in facing the shock that occurs.
The SLR findings also reveal that most studies assessing urban resilience tend to focus on the city level, rather than broader spatial scales, such as global, national, or regional levels, or narrower ones, such as local communities or individual societies. This trend can be attributed to the spatial heterogeneity of resilience-building processes, where influencing factors vary depending on the scale [23,109]. At larger scales, the number of influencing factors increases, making the system more complex [47]. Therefore, the higher the spatial scale, the more complex the system becomes. Conversely, using smaller spatial scales allows for clearer and more manageable resilience assessments. As noted by [23], each resilience issue is associated with a specific spatial scale. For instance, at the national or regional level, topics such as climate change, economic concerns, and institutional factors are commonly addressed (see Table 3).
The selection of a study’s spatial scale also influences the research methodology. Studies conducted at the community or society scale approach, often through case studies, typically use qualitative methods, as the smaller scale allows for more in-depth exploration and detailed understanding of how resilience develops—something less feasible at broader spatial scales.
Resilience measurement indicators are influenced by the type of shock experienced. For instance, in the case of natural disasters, such as floods, the independent variables used as indicators may include contributing factors, such as topography, the amount of green open space, flood levels, urban sprawl, population growth, and changes in river width. By observing these driving factors, cities can assess the extent of their resilience, identify critical areas of weakness, and identify actions and programs to improve resilience.
In general, the relationship between methods, spatial scales and indicators in evaluating urban resilience assessment can be concluded from Table 7.

5. Conclusions

A systematic literature review of urban resilience in metropolitan areas revealed three main thematic clusters: environmental issues, urban planning and social–human factors. This means that urban resilience research highlights the need for interdisciplinary frameworks that combine environmental management, strategic urban planning, and community engagement to make regions more resilient. There has been a significant increase in research on urban resilience in metropolitan areas since 2010, with more than 70% of articles discussing resilience at the city scale and more than 50% using a quantitative approach. This study shows a trend of increasing attention to various disaster issues, especially due to the impact of climate change, economic shocks, socio–environmental issues and the COVID-19 pandemic that have occurred in recent years, which have affected urban resilience.
Metropolitan areas in Asia, especially countries in East and South Asia, are the main focus in this literature not only because of its exposure to multiple risks but also due to its unique socio–spatial dynamics. The peri-urban and desakota zones, in particular, warrant special attention as they may represent the weakest links in the urban resilience chain. To effectively address these issues, resilience assessments must shift toward a smaller-scale focus, encompassing local, community, and individual levels. Such an approach is essential to uncover nuanced urban problems that are often obscured in macro-level analyses. In turn, this localized understanding can inform more adaptive, inclusive, and sustainable urban spatial planning policies.
Future research should place greater emphasis on urban resilience at the local or suburban scale, particularly in the fringe areas of Asian metropolitan regions, where resilience levels are generally lower. A mixed-methods approach that integrates both quantitative and qualitative techniques can offer a more holistic understanding of the performance and capacity of urban systems in these areas. Dimension of resilience will be focused not only on socio–ecological, economic, and infrastructure dimensions but also issues of wealth, income, livelihoods, well-being, inclusion and social networks will be elaborated. One of the potential directions is conducting longitudinal studies in desakota zones, which are experiencing continuous transformation. Such studies are vital for tracking how resilience evolves or diminishes over time due to urban growth, population movement, environmental pressures, and changing governance structures. Another promising area of research involves examining the integration of governance and social capital indicators. In these fringe zones, where formal governance may be weak or fragmented, social capital often plays a key role in adaptation.

Author Contributions

Conceptualization, Y.S., E.R., A.E.P. and B.B.; Methodology, E.R., A.E.P. and B.B.; Data curation, Y.S.; Writing—original draft, Y.S.; Writing—review & editing, E.R., A.E.P. and B.B.; Supervision, E.R., A.E.P. and B.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Selection of indicators for assessing urban resilience in metropolitan areas around the world.
Table A1. Selection of indicators for assessing urban resilience in metropolitan areas around the world.
DimensionSpatial ScaleShockAnalysisIndicatorReferences
Socio-Economic Community Climate ChangeFactors that influenceAge, generation group, education, income[74]
Regional and city Earthquake, climate change and COVID-19Descriptive analysis and trendsPoverty, multidimensional poverty, potential lives lost, infant mortality, municipal expenditure, COVID-19 infected, COVID-19 deaths[110]
CityOpioid overdose crisisResilience index or vulnerability indexObserved versus predicted opioid overdose mortality rates, availability of health and social services, community mobilization efforts, and community attitudes toward addiction.[111]
CityNatural DisastersCity resilience indexPopulation census, financial independence ratio, local tax revenues, percentage of economically active population, population, percentage of population over 65 years of age[112]
CityEconomic downturn and outmigrationEconomic resilience indexDiversity (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]
EconomicCityCOVID-19 PandemicCity resilience indexGDP per capita, proportion of tertiary industry in GDP, realization of foreign capital utilization, urban per capita income, income in the general public budget[114]
CityEconomic recessionEconomic capacity, socio–demographic capacity, and connectivity capacity CommunityIncome equality, economic diversity, affordability, business environment, educational attainment, health insurance rates, civic infrastructure, metropolitan stability, and voter turnout.[115]
CityEconomic fluctuationsTemporal development of urban resilienceGDP per capita, GDP growth rate, total fixed asset investment[116]
Citynatural disasters (rain, storm, typhoon)urban resilience indexemployment 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]
CityNatural disastersUrban and rural resilience indexHome ownership, employment rate, racial/ethnic income equality, primary sector/tourism independence, gender income equality, business size, large-scale distribution retail-regional, federal employment[30]
CityCOVID-19 Urban resilience indexAnnual 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]
CityRapid urbanizationCity resilience indexGDP 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]
CityClimate changeUrban resilience indexGDP 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]
SocialLocalFloodResilience indexPopulation density, per capita income, inadequate sanitation[58]
District FloodsInfluencing factorsHuman (population density, age, ethnic disparities, disability), community (health access, population well-being, migration), organization (administrative work, regional accessibility, housing capacity)[61]
Citywater droughtCity blueprint Approach consists of: Trends and Pressures Framework (TPF)TPF = social pressure (urbanization rate, disease burden, education level, political instability), [119]
Citysocial disparitiesTemporal development of city resiliencenumber of hospital beds per 10,000 people, number of higher education students per 10,000 people, registered unemployment rate in urban areas[116]
Citynatural disasters (rain, storms, typhoons)City resilience index and analysis of inhibitingpopulation 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]
CityNatural disastersUrban and rural resilienceIndex 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]
CityCOVID-19 pandemicCity resilience indexNumber of students on campus, number of beds in health facilities, percentage of non-agricultural employment, registered urban unemployment rate[114]
CityCOVID-19 pandemicCity resilience indexPopulation 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]
CityRapid UrbanizationCity resilience indexNumber of students in regular schools and universities, number of hospital beds per 1000 population[118]
CityClimate changeCity resilience indexAbility 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]
EcologicalCityUrbanizationecological resilience indexpollution load, environmental quality, landscape form[120]
Citywater shortageEcological resilience index (resistance, adaptability, resilience), influencing factors, evaluation and spatiotemporal evolution of water poverty characteristicsresistance (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]
Cityrapid urbanizationecological network resilience (ecological resistance, network analysis index)land use type, vegetation cover, geographic feature information[121]
Cityurbanization and climate changeurbanization and climate change landscape ecological risk assessment (LERA): potential, connectivity and resiliencepotential (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]
Citywater droughtThe 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]
Cityincreasing population density, floodingimpact on population growth, built-up area expansion, infrastructure pressure, flood risk exposure, and loss of agricultural land until 2050percentage of population increase, built-up area growth, population density, conversion of agricultural land area, and number of people exposed to flood risk zones.[122]
Cityecological degradationTemporal development of urban resiliencegreen coverage level of built-up areas, green area of parks per capita, level of non-hazardous domestic waste treatment[116]
Citynatural disasters (rain, storm, typhoon)Urban resilience index and analysis of inhibiting factorsnumber of regional parks, green area of parks, green area of green space, river area[117]
CityNatural disastersCity and village resilience indexLocal food suppliers, natural flood buffers, efficient energy use, permeable surfaces, efficient water use[30]
CityNatural disastersCity resilience indexPercentage 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]
CityCOVID-19 pandemicCity resilience indexLevel 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]
CityCOVID-19 pandemicCity resilience indexGreen areas, green coverage in built-up areas, public green areas, land area, industrial wastewater discharge, industrial sulfur dioxide emissions[57]
CityRapid urbanizationCity resilience indexCoverage level of green open space in built-up areas, Area of green open space parks per capita, Wastewater discharge per capita[118]
CityClimate changeCity resilience indexRatio of environmental expenditure to fiscal expenditure, percentage of green forest area (or green area per capita in urban areas),[73]
Physical/InfrastructureLocalFloodsResilience indexFlood depth and flood duration factors[58]
Citytraffic congestioncongestion index to assess traffic vulnerability and resilience of transportation systemstraffic volume (vehicles/hour), degree of saturation (ratio), and congestion index[123]
CityFloodImpact of flood policy, governance, and urban planning on flood resilienceflood elevation, urban expansion, population growth, river width changes, and topography[124]
CityInfrastructure vulnerabilityTemporal development of urban resilienceroad area per capita, gas penetration rate, drainage pipe density[116]
Citynatural disasters (rain, storm, typhoon)Urban resilience index and analysis of inhibiting factorsdrainage 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]
CityNatural disastersUrban and rural resilience indexMore 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]
CityClimate changeCity resilience indexAbility to manage urban risks, waterlogging points in urban areas, traffic congestion index, public health facilities per capita, broadcasting and television coverage[73]
CityNatural DisastersCity resilience indexAverage 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]
CityCOVID-19 pandemicCity resilience indexUrban road area per capita, urban drainage pipe density, annual electricity consumption, goods traffic on highways, Internet broadband access users[114]
CityCOVID-19 pandemicCity resilience indexNumber 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]
CityRapid urbanizationCity resilience indexroad 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]
LocalCOVID-19 pandemicPotential risk location of transmissionNumber 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]
LocalCOVID-19 pandemicConsistency Index and consistency ratio1. 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]
InstitutionalCityclimate changeinstitutional capacity assessmentengagement, mainstreaming, monitoring and evaluation, investment, information, knowledge, innovation and learning, skills and expertise, local content sensitivity, implementation[125]
CityHurricane CERNL’s role in rebuilding basic services and infrastructure, assessing the effectiveness of the board in a fragmented institutional frameworkspeed of service recovery, level of infrastructure repair, level of stakeholder participation, and functionality of governance structures during the recovery process[52]
Citywater droughtCity 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]
Cityinstitutional weaknessesTemporal development of city resiliencenumber of social security participants, number of community service facilities, number of public management employees and social organizations[116]
CityNatural disastersCity and village resilience indexMitigation 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]

References

  1. Halbreich, U. Impact of Urbanization on Mental Health and Wellbeing. Curr. Opin. Psychiatry 2023, 36, 200–205. [Google Scholar] [CrossRef]
  2. Adlakha, D.; John, F. The Future is Urban: Integrated Planning Policies can enable Healthy and Sustainable Cities. Lancet Glob. Health 2022, 10, e790–e791. [Google Scholar] [CrossRef] [PubMed]
  3. Rustiadi, E.; Pribadi, D.O.; Pravitasari, A.E.; Indraprahasta, G.S.; Imam, L.S. Jabodetabek Megacity: From City Development Urban Complex Management System; Springer: Berlin/Heidelberg, Germany, 2015; Chapter 22. [Google Scholar]
  4. Berbeć, A.K. Agricultural resilience and agricultural sustainability—Which is which? Curr. Agron. 2024, 53, 10–22. [Google Scholar] [CrossRef]
  5. Sutton, J.; Arku, G. Regional Economic Resilience: Towards a system approach. Reg. Stud. Reg. Sci. 2022, 9, 497–512. [Google Scholar] [CrossRef]
  6. Zhang, X.; Li, H. Urban resilience and urban sustainability: What we know and what do not know? Cities 2018, 72, 141–148. [Google Scholar] [CrossRef]
  7. Bourne, L.S. (Ed.) Internal Structure of the City: Readings on Space and Environment; Oxford University Press: New York, NY, USA, 1971; ISBN 0195013212. [Google Scholar]
  8. McGee, T.G. Building liveable cities in Asia int the Twenty—First Century research and Policy Challenge for the urban future of Asia. Malays. J. Environ. Manag. 2010, 11, 14–28. [Google Scholar]
  9. Berkes, F.; Ross, H. Panarchy and community resilience: Sustainability science and policy implications. Environ. Sci. Policy 2016, 61, 185–193. [Google Scholar] [CrossRef]
  10. Klein, R.J.; Nicholls, R.J.; Thomalla, F. Resilience to natural hazards: How useful is this concept? Glob. Environ. Change Part B Environ. Hazards 2003, 5, 35–45. [Google Scholar] [CrossRef]
  11. Liu, W.; Zhou, J.; Li, X.; Zheng, H.; Liu, Y. Urban resilience and its spatial correlation from multidimensional perspective: A case study of four province North-South Seismic Belt, China. Sustain. Cities Soc. 2024, 101, 105109. [Google Scholar] [CrossRef]
  12. Dalziell, E.P.; McManus, S.T. Resilience, Vulnerability and Adaptive Capacity: Implications for Sistems Performance. International Forum for Engineering Decision Making (IFED); Switzerland. December 2004. Available online: https://www.resorgs.org.nz/wp-content/uploads/2017/07/ifed_dec04_edsm.pdf (accessed on 28 February 2025).
  13. Amirzadeh, M.; Sobhaninia, S.; Sharifi, A. Urban resilience: Vague or not an evolutionary concept? Sustain. Cities Soc. 2022, 81, 103853. [Google Scholar] [CrossRef]
  14. Shi, Y.; Zhang, T.; Jiang, Y. Digital economy, technological innovation and urban resilience. Sustainability 2023, 15, 9250. [Google Scholar] [CrossRef]
  15. Rockefeller Foundation and Arup, City Resilience Index: Research Report Volume 1 Desk Study, April 2014 (New York and London: The Rockefeller Foundation: With Ove Arup & Partners International). 2014. Available online: https://www.arup.com/globalassets/downloads/insights/city-resilience-index.pdf (accessed on 5 August 2024).
  16. United Nations International Strategy for Disaster Reduction (UNISDR), Living with Risk a Global Review of Disaster Reduction Initiatives, 2004 Version—Volume II Annexes. Available online: https://disasterlaw.ifrc.org/media/3141 (accessed on 5 August 2024).
  17. Twigg, J. Characteristics of A Disaster—Resilient Community, Research Gate. 2007. Available online: https://www.preventionweb.net/files/2310_Characteristicsdisasterhighres.pdf (accessed on 5 August 2024).
  18. Cutter, S. L.; Barnes, L.; Berry, M.; Burton, C.; Evans, E.; Tate, E.; Webb, J. A place-based model for understanding community resilience to natural disasters. Glob. Environ. Change 2008, 18, 598–606. [Google Scholar] [CrossRef]
  19. Adger, W.N. Social and ecological resilience: Are they related? Prog. Hum. Geogr. 2000, 24, 347–364. [Google Scholar] [CrossRef]
  20. Obrist, B.; Pfeiffer, C.; Henley, R. Multi-layered social resilience: A new approach in mitigation research. Prog. Dev. Stud. 2010, 10, 283–293. [Google Scholar] [CrossRef]
  21. Xiao, J.; Boschma, R.; Andersson, M. Resilience in the European Union: The effect of the 2008 crisis on the ability of regions in Europe to develop new industrial specializations. Ind. Corp. Change 2017, 27, 15–47. [Google Scholar] [CrossRef]
  22. Peng, C.; Yuan, M.; Gu, C.; Peng, Z.; Ming, T. A review of the theory and practice of regional resilience. Sustain. Cities Soc. 2017, 29, 86–96. [Google Scholar] [CrossRef]
  23. Masik, G. The Concept of Resilience: Dimensions, Properties of Resilient Systems and Spatial Scales of Resilience. Geogr. Pol. 2022, 95, 295–310. [Google Scholar] [CrossRef]
  24. Sutton, J.; Arcidiacono, A.; Torrisi, G.; Arku, R.N. Regional Economic Resilience: A Scoping Review. Prog. Hum. Geogr. 2023, 47, 500–532. [Google Scholar] [CrossRef]
  25. Büyüközkan, G.; Ilıcak, Ö.; Feyzioğlu, O. A review of urban resilience literature. Sustain. Cities Soc. 2021, 77, 103579. [Google Scholar] [CrossRef]
  26. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement : An updated guideline for reporting systematic reviews. BMJ 2021, 372, 71. [Google Scholar] [CrossRef]
  27. De Jong, M.; Joss, S.; Schraven, D.; Zhan, C.; Weijnen, M. Sustainable-Smart-Resilient-Low Carbon-Eco-Knowledge Cities; Making Sense of a Multitude of Concepts Promoting Sustainable Urbanization. J. Clean. Prod. 2015, 109, 25–38. [Google Scholar] [CrossRef]
  28. Pickett, S.T.A.; Cadenasso, M.L.; Grove, J.M. Resilient Cities: Meaning, Models, and Metaphor for Integrating the Ecological, Socio-Economic, and Planning Realms. Landsc. Urban Plan. 2004, 69, 369–384. [Google Scholar] [CrossRef]
  29. Li, G.; Kou, C.; Wang, Y.; Yang, H. System Dynamics Modelling for Improving Urban Resilience in Beijing, China. Resour. Conserv. Recycl. 2020, 161, 104954. [Google Scholar] [CrossRef]
  30. Cutter, S.L.; Ash, K.D.; Emrich, C.T. Urban–Rural Differences in Disaster Resilience. Ann. Am. Assoc. Geogr. 2016, 106, 1236–1252. [Google Scholar] [CrossRef]
  31. Lal, R. Home Gardening and Urban Agriculture for Advancing Food and Nutritional Security in Response to the COVID-19 Pandemic. Food Secur. 2020, 12, 871–876. [Google Scholar] [CrossRef] [PubMed]
  32. Zhang, D.-M.; Du, F.; Huang, H.; Zhang, F.; Ayyub, B.M.; Beer, M. Resiliency assessment of urban rail transit networks: Shanghai metro as an example. Saf. Sci. 2018, 106, 230–243. [Google Scholar] [CrossRef]
  33. Alvarez, M.K.; Cardenas, K. Evicting Slums, ‘building Back Better’: Resiliency Revanchism and Disaster Risk Management in Manila. Int. J. Urban Reg. Res. 2019, 43, 227–249. [Google Scholar] [CrossRef]
  34. Sharma, A.; Conry, P.; Fernando, H.J.S.; Hamlet, A.F.; Hellmann, J.J.; Chen, F. Green and Cool Roofs to Mitigate Urban Heat Island Effects in the Chicago Metropolitan Area: Evaluation with a Regional Climate Model. Environ. Res. Lett. 2016, 11, 064004. [Google Scholar] [CrossRef]
  35. Bertilsson, L.; Wiklund, K.; Tebaldi, I.d.M.; Rezende, O.M.; Veról, A.P.; Miguez, M.G. Urban Flood Resilience—A Multi-Criteria Index to Integrate Flood Resilience into Urban Planning. J. Hydrol. 2019, 573, 970–982. [Google Scholar] [CrossRef]
  36. Lyu, H.M.; Sun, W.J.; Shen, S.L.; Arulrajah, A. Flood Risk Assessment in Metro Systems of Mega-Cities Using a GIS-Based Modeling Approach. Sci. Total. Environ. 2018, 626, 1012–1025. [Google Scholar] [CrossRef]
  37. Xiang, Z.; Qin, H.; He, B.J.; Han, G.; Chen, M. Heat Vulnerability Caused by Physical and Social Conditions in a Mountainous Megacity of Chongqing, China. Sustain. Cities Soc. 2022, 80, 103792. [Google Scholar] [CrossRef]
  38. Fiksel, J.; Sanjay, P.; Raman, K. Steps toward a Resilient Circular Economy in India. Clean Technol. Environ. Policy 2021, 23, 203–218. [Google Scholar] [CrossRef] [PubMed]
  39. Luo, F.; Liu, Y.; Peng, J.; Wu, J. Assessing Urban Landscape Ecological Risk through an Adaptive Cycle Framework. Landsc. Urban Plan. 2018, 180, 125–134. [Google Scholar] [CrossRef]
  40. Xu, C.; Li, B.; Kong, F.; He, T. Spatial-Temporal Variation, Driving Mechanism and Management Zoning of Ecological Resilience Based on RSEI in a Coastal Metropolitan Area. Ecol. Indic. 2024, 158, 111447. [Google Scholar] [CrossRef]
  41. Das, M.; Das, A.; Pereira, P.; Mandal, A. Exploring the Spatio-Temporal Dynamics of Ecosystem Health: A Study on a Rapidly Urbanizing Metropolitan Area of Lower Gangetic Plain, India. Ecol. Indic. 2021, 125, 107584. [Google Scholar] [CrossRef]
  42. Georgeson, L.; Maslin, M.; Poessinouw, M.; Howard, S. Adaptation Responses to Climate Change Differ between Global Megacities. Nat. Clim. Chang. 2016, 6, 584–588. [Google Scholar] [CrossRef]
  43. Rahman, K.M.A.; Zhang, D. Analyzing the Level of Accessibility of Public Urban Green Spaces to Different Socially Vulnerable Groups of People. Sustainability 2018, 10, 3917. [Google Scholar] [CrossRef]
  44. Xiang, L.; Cai, M.; Ren, C.; Ng, E. Modeling Pedestrian Emotion in High-Density Cities Using Visual Exposure and Machine Learning: Tracking Real-Time Physiology and Psychology in Hong Kong. Build. Environ. 2021, 205, 108273. [Google Scholar] [CrossRef]
  45. Falco, S.d.; Angelidou, M.; Addie, J.P.D. From the ‘Smart City’ to the ‘Smart Metropolis’? Building Resilience in the Urban Periphery. Eur. Urban Reg. Stud. 2019, 26, 205–223. [Google Scholar] [CrossRef]
  46. Fan, C.; Jiang, X.; Lee, R.; Mostafavi, A. Equality of Access and Resilience in Urban Population-Facility Networks. npj Urban Sustain. 2022, 2, 1–12. [Google Scholar] [CrossRef]
  47. Zevenbergen, C.; Veerbeek, W.; Gersonius, B.; Van Herk, S. Challenges in Urban Flood Management: Travelling Across Spatial and Temporal Scales. J. Flood Risk Manag. 2008, 1, 81–88. [Google Scholar] [CrossRef]
  48. Borrelli, N.; Mela, A.; Guerrero, S.F.B. Dancing in the dark: How food governance can support resilience in Portland, Oregon. Food Cult. Soc. 2022, 26, 685–708. [Google Scholar] [CrossRef]
  49. Hestad, D.; Tàbara, J.D.; Thornton, T.F. The role of sustainability-oriented hybrid organisations in the development of transformative capacities: The case of Barcelona. Cities 2021, 119, 103365. [Google Scholar] [CrossRef]
  50. Wagenaar, H.; Wilkinson, C. Enacting Resilience: A Performative Account of Governing for Urban Resilience. Urban Stud. 2015, 52, 1265–1284. [Google Scholar] [CrossRef]
  51. Badhan, I.M.; Siddika, A. Evaluating the policy outcomes for urban resiliency in informal settlements since independence in Dhaka, Bangladesh: A review. Nakhara J. Environ. Des. Plan. 2019, 17, 97–110. [Google Scholar] [CrossRef]
  52. Aguilar-Barajas, I.; Ramirez, A.I. Recovering of the Monterrey Metropolitan Area, Mexico, After Hurricane Alex (2010): The Role of the Nuevo Leon State Reconstruction Council. Front. Environ. Sci. 2019, 7, 163. [Google Scholar] [CrossRef]
  53. Gavari-Starkie, E.; Casado-Claro, M.-F.; Navarro-González, I. The Japanese Educational System as an International Model for Urban Resilience. Int. J. Environ. Res. Public Health 2021, 18, 5794. [Google Scholar] [CrossRef]
  54. Jozaei, J.; Mitchell, M. An assessment for developing resilience, capacity of Tasmanian coastal governance. Ocean. Coast Manag. 2018, 163, 130–140. [Google Scholar] [CrossRef]
  55. Ling, T.-Y.; Chiang, Y.-C. Strengthening the resilience of urban retailers towards flood risks—A case study in the riverbank region of Kaohsiung City. Int. J. Disaster Risk Reduct. 2018, 27, 541–555. [Google Scholar] [CrossRef]
  56. Roach, E.L.; Al-Saidi, M. Rethinking infrastructure rehabilitation: Conflict resilience of urban water and energy supply in the Middle East and South Sudan. Energy Res. Soc. Sci. 2021, 76, 102052. [Google Scholar] [CrossRef]
  57. Chen, X.; Quan, R. A Spatiotemporal Analysis of Urban Resilience to the COVID-19 pandemic in the Yangtze River Delta. Nat. Hazards 2021, 106, 829–854. [Google Scholar] [CrossRef] [PubMed]
  58. Miguez, M.G.; Veról, A.P. A Catchment Scale Integrated Flood Resilience Index to Support Decision Making in Urban Flood Control De-sign. Environ. Plan. B Urban Anal. City Sci. 2016, 44, 925–946. [Google Scholar] [CrossRef]
  59. Chen, T.L.; Li, Y.E. Building Urban Resilience: Lessons from the COVID-19 Pandemic for Future-Proofing City Infrastructure. J. Urban Manag. 2024, in press. [Google Scholar] [CrossRef]
  60. Wan, G.; Sun, D.; Peng, B.; Mao, X. Risk Assessment of Urban Transportation Complex Hub from Resilience Perspective: An Empirical Study on Xi’an North Railway Station. Nat. Hazards Rev. 2024, 25, 04024042. [Google Scholar] [CrossRef]
  61. Chun, H.; Chi, S.; Hwang, B.G. A Spatial Disaster Assessment Model of Social Resilience Based on Geographically Weighted Regression. Sustainability 2017, 9, 12. [Google Scholar] [CrossRef]
  62. Haiqi, Z. Analysis of Spatiotemporal Evolution and Influencing Factors of Water Poverty and Ecological Resilience Coupling Coordination in Chinese. Res.Sq. 2024. [Google Scholar] [CrossRef]
  63. Pribadi, D.O.; Saifullah, K.; Putra, A.S.; Nurdin, M.; Iman, L.O.S.; Rustiadi, E. Spatial Analysis of COVID-19 Outbreak for Assess the Effectiveness of Social Restriction Policy in Dealing with the Pandemic in Jakarta. Spat. Spatio-Temporal Epidemiol. 2021, 39, 100454. [Google Scholar] [CrossRef]
  64. Lhomme, S.; Serre, D.; Diab, Y.; Laganier, R. Analyzing resilience of urban networks: A preliminary step towards more flood resilient cities. Nat. Hazards Earth Syst. Sci. 2013, 13, 221–230. [Google Scholar] [CrossRef]
  65. Li, Y.; Shi, Y.; Qureshi, S.; Bruns, A.; Zhu, X. Applying the concept of spatial resilience to socio-ecological systems in the urban wetland interface. Ecol. Indic. 2014, 42, 135–146. [Google Scholar] [CrossRef]
  66. Meerow, S.; Newell, J.P. Spatial planning for multifunctional green infrastructure: Growing resilience in Detroit. Landsc. Urban Plan 2017, 159, 62–75. [Google Scholar] [CrossRef]
  67. Therrien, M.C.; Jutras, M.; Usher, S. Including quality in Social network analysis to foster dialogue in urban resilience and adaptation policies. Environ. Sci. Policy 2019, 93, 1–10. [Google Scholar] [CrossRef]
  68. Cui, P.; Li, D. A SNA-based methodology for measuring the community resilience from the perspective of social capitals: Take Nanjing, China as an example. Sustain. Cities Soc. 2020, 53, 101880. [Google Scholar] [CrossRef]
  69. McClymont, K.; Cunha, D.G.F.; Maidment, C.; Ashagre, B.; Vasconcelos, A.F.; de Macedo, M.B.; dos Santos, M.F.N.; Júnior, M.N.G.; Mendiondo, E.M.; Barbassa, A.P.; et al. Towards urban resilience through Sustainable Drainage Systems: A multi-objective optimisation problem. J. Environ. Manag. 2020, 275, 111173. [Google Scholar] [CrossRef] [PubMed]
  70. Liao, T.; Hu, T.; Ko, Y. A resilience optimization model for transportation networks under disasters. Nat. Hazards 2018, 93, 469–489. [Google Scholar] [CrossRef]
  71. Datola, G.; Bottero, M.; De Angelis, E. How Urban Resilience Can Change Cities: A System Dynamics MODEL Approach; Springer International Publishing: Cham, Switzerland, 2019; pp. 108–122. [Google Scholar]
  72. Mou, Y.; Luo, Y.; Su, Z.; Wang, J.; Liu, T. Evaluating the dynamic sustainability and resilience of a hybrid urban system: Case of Chengdu. China J. Clean. Prod. 2021, 291, 125719. [Google Scholar] [CrossRef]
  73. Zheng, Y.; Xie, X.L.; Lin, C.Z.; Wang, M. Development as adaptation: Framing and Measuring Urban Resilience in Beijing, Scient Direct. Adv. Clim. Change Res. 2018, 9, 234–242. [Google Scholar] [CrossRef]
  74. Boafo, Y.A.; Amankwaa, E.F.; Spataru, C.; Carvalho, P. It Is Getting Too Hot Lately’: Urban Households’ Knowledge, Experiences and Governance of Extreme Heat Events in Accra, Ghana. Urban Clim. 2025, 59, 102287. [Google Scholar] [CrossRef]
  75. Matsumoto, T. Strengthening Urban Resilience/Disaster Risk Management in Asian Cities. In Resilient Policies in Asian Cities; Tanaka, M., Baba, K., Eds.; Springer: Singapore, 2020. [Google Scholar] [CrossRef]
  76. Bixler, R.P.; Lieberknecht, K.; Atshan, S.; Zutz, C.P.; Richter, S.M.; Belaire, J.A. Reframing urban governance for resilience implementation: The role of networkclosure and other insights from a network approach. Cities 2020, 103, 102726. [Google Scholar] [CrossRef]
  77. Pan, Y.; Liu, J.; Cheng, C. Research on Urban Resilience from the Perspective of Land Intensive Use: Indicator Measurement, Impact and Policy Implications. Buildings 2024, 14, 2564. [Google Scholar] [CrossRef]
  78. Ning, L.; Sheng, S.; Meng, Y. The interplay and synergistic relationship between urban land expansion and urban resilience across the three principal metropolitan regions of the Yangtze River Basin. Sci. Rep. 2024, 14, 31868. [Google Scholar] [CrossRef]
  79. Gómez-Baggethun, E.; Gren, Å.; Barton, D.; Langemeyer, J.; McPhearson, T.; O’Farrell, P.; Andersson, E.; Hamstead Zoé, A.; Kremer, P. Urban Ecosystem Services. In Urban Ecology for Citizens and Planners; University Press of Florida: Gainesville, FL, USA, 2021. [Google Scholar]
  80. Croci, E.; Lucchitta, B. Nature-based solutions (NBSs) for urban resilience. Introduction. Econ. Policy Energy Environ. 2019, 31–42. [Google Scholar] [CrossRef]
  81. Marques, A.L.; Alvim, A.T.B. Metropolitan fringes as strategic areas for urban resilience and sustainable transitions: Insights from Barcelona Metropolitan Area. Environ. Sci. Geogr. 2024, 150, 105018. [Google Scholar] [CrossRef]
  82. Sharma, M.; Sharma, B.; Kumar, N.; Kumar, A. Establishing Conceptual Components for Urban Resilience: Taking Clues from Urbanization through a Planner’s Lens. Nat. Hazards Rev. 2023, 24, 04022040. [Google Scholar] [CrossRef]
  83. Kawamoto, K.; Tontisirin, N.; Yamashita, E.Y. The Structural Analysis of Virtual Social Capital for Urban Resilience in a Metropolitan Area: The case of Tokyo and Bangkok, Nakhara. J. Environ. Des. Plan. 2021, 20, 101. [Google Scholar] [CrossRef]
  84. Yao, Y.; Guo, Z.; Huang, X.; Ren, S.; Hu, Y.; Dong, A.; Guan, Q. Gauging urban resilience in the United States during the COVID-19 pandemic via social network analysis. Cities 2023, 138, 104361. [Google Scholar] [CrossRef] [PubMed]
  85. Karl, H.; Scarlett, L.; Kirshen, P.; Dell, R.; Ibrahim, H.; Kuhl, L.; Mosher, T.; Navarro, B.; Rising, M.; Towery, N. Adapting to changing climate: Exploring the role of the neighborhood. In Restoring Lands—Coordinating Science, Politics and Action: Complexities of Climate and Governance Book Chapter2012; Springer: Dordrecht, The Netherlands, 2012. [Google Scholar] [CrossRef]
  86. Wallace, D.; Wallace, R. Urban systems during disasters: Factors for resilience. Ecol. Soc. 2008, 13, 14. [Google Scholar] [CrossRef]
  87. Pierce, G.; Gabbe, C.; Dunlap, L.; Detwiler, B.; Garcia, P.U.; Hagen, H.; Schmidt, K. Planning for heat beyond the big city: Comparing smaller cities’ heat activities, opportunities, and constraints in California. Local Environ. 2025, 1–17. [Google Scholar] [CrossRef]
  88. Meerow, S.; Keith, L. Planning for Extreme Heat. J. Am. Plan. Assoc. 2021, 88, 319–334. [Google Scholar] [CrossRef]
  89. Kearl, Z.; Vogel, J. Urban extreme heat, climate change, and saving lives: Lessons from Washington state. Urban Clim. 2023, 47, 101392. [Google Scholar] [CrossRef]
  90. Lo, A.Y.; Xu, B.; Chan, F.; Su, R. Household economic resilience to catastrophic rainstorms and flooding in a Chinese megacity. Geogr. Res. 2016, 54, 406–419. [Google Scholar] [CrossRef]
  91. Xian, S.; Yin, J.; Lin, N.; Oppenheimer, M. Influence of risk factors and past events on flood resilience in coastal megacities: Comparative analysis of NYC and Shanghai. Sci. Total. Environ. 2018, 610–611, 1251–1261. [Google Scholar] [CrossRef]
  92. Liu, X.; Li, S.; Xu, X.; Luo, J. Integrated natural disasters urban resilience evaluation: The case of China. Nat. Hazards 2021, 107, 2105–2122. [Google Scholar] [CrossRef]
  93. Ma, Y.; Jiang, Y. Ecosystem-based adaptation to address urbanization and climate change challenges: The case of China’s sponge city initiative. Clim. Policy 2022, 23, 268–284. [Google Scholar] [CrossRef]
  94. Zhao, R.; Fang, C.; Liu, J.; Zhang, L. The evaluation and obstacle analysis of urban resilience from the multidimensional perspective in Chinese cities. Sustain. Cities Soc. 2022, 86, 104160. [Google Scholar] [CrossRef]
  95. Capotorti, G.; Mollo, B.; Zavattero, L.; Anzellotti, I.; Celesti-Grapow, L. Setting Priorities for Urban Forest Planning. A Comprehensive Response to Ecological and Social Needs for the Metropolitan Area of Rome (Italy). Sustainability 2015, 7, 3958–3976. [Google Scholar] [CrossRef]
  96. Assumma, V.; Bottero, M.; Datola, G.; Pezzoli, A.; Quagliolo, C. Climate Change and Urban Resilience. Preliminary Insights from an Integrated Evaluation Framework. In New Metropolitan Perspectives; Springer International Publishing: Cham, Switzerland, 2020. [Google Scholar]
  97. Caldarice, O.; Tollin, N.; Pizzorni, M. The relevance of science-policy-practice dialogue. Exploring the urban climate resilience governance in Italy. City Territ. Archit. 2021, 8, 9. [Google Scholar] [CrossRef]
  98. Hung, C.H.; Hung, H.C.; Hsu, M.C. Linking the interplay of resilience, vulnerability, and adaptation to long-term changes in metropolitan spaces for climate-related disaster risk management. Clim. Risk Manag. 2024, 44, 100618. [Google Scholar] [CrossRef]
  99. Cavallaro, E.; Sessa, M.R.; Malandrino, O. Renewable Energy Communities in the Energy Transition Context. Int. J. Energy Econ. Policy 2023, 13, 408–417. [Google Scholar] [CrossRef]
  100. Antonazzi, E.; Di Lorenzo, G.; Stracqualursi, E.; Araneo, R. Renewable Energy Communities for Sustainability: A Case Study in the Metropolitan Area of Rome. In Proceedings of the 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Madrid, Spain, 6–9 June 2023; pp. 1–6. [Google Scholar] [CrossRef]
  101. Vallati, A.; Basso, G.L.; Muzi, F.; Fiorini, C.V.; Pastore, L.M.; Di Matteo, M. Urban Energy Transition: Sustainbale model simulation for social house district. Energy 2024, 308, 132611. [Google Scholar] [CrossRef]
  102. Sharifi, A. The COVID-19 Pandemic: Lessons for Urban Resilience. In COVID-19: Systemic Risk and Resilience. Risk, Systems and Decisions; Linkov, I., Keenan, J.M., Trump, B.D., Eds.; Springer Nature: Cham, Switzerland, 2021. [Google Scholar]
  103. Balland, P.; Rigby, D.; Boschma, R. The Technological Resilience of U.S. Cities. Camb. J. Reg. Econ. Soc. 2015, 8, 167–184. [Google Scholar] [CrossRef]
  104. Chan, F.K.S.; Mitchell, G.; Adekola, O.; McDonald, A. Flood risk in Asia’s urban mega-deltas: Drivers, impacts, and response. Env. Urban Asia 2012, 3, 41–61. [Google Scholar] [CrossRef]
  105. Swerts, E.; Denis, E. Chapter: Megacities: The Asian Era. In Urban Development Challenges, Risks and Resilience in Asian Mega Cities; Springer: Tokyo, Japan, 2015; pp. 1–28. [Google Scholar]
  106. McGee, T.G. The Emergence of desakota regions in Asia: Expanding a hypothesis. In The Extended Metropolis: Settlement Transition in Asia, Ginsburg, N., Koppel, B., McGee, T.G., Eds.; University of Hawaii Press: Honolulu, HI, USA, 1991; pp. 3–26. [Google Scholar]
  107. Pang, P.; Guo, Z.; Chen, W.Y. Assessing Urban-Rural Climate Resilience of Metropolitan Yangon, Myanmar. Singap. J. Trop. Geogr. 2021, 42, 451–468. [Google Scholar] [CrossRef]
  108. Douglass, M. Planning for Environmental Sustainability int the Extended Jakarta Metropolitan Region. In Part III: Studies of Japan, India and Java in The Extended Metropolis Settlement Transition in Asia; University of Hawaii Press: Honolulu, HI, USA, 1991. [Google Scholar]
  109. Carpenter, S.R.; Brock, W.A. Spatial Complexity, Resilience and Policy Diversity : Fishing on Lake-Rich Landscapes. Ecol. Soc. 2004, 9, 8. [Google Scholar] [CrossRef]
  110. Barton, J.R.; Gutiérrez-Antinopai, F.; Ulloa, M.E. Adaptive Capacity as Local Sustainable Development: Contextualizing and Comparing Risks and Resilience in Two Chilean Regions. Sustainability 2021, 13, 4660. [Google Scholar] [CrossRef]
  111. Hochstetler, A.; Peters, D.J.; Monnat, S.M. Prescription Opioid Resiliency and Vulnerability: A Mixed-Methods Comparative Case Study. Am. J. Crim. Justice 2022, 47, 651–671. [Google Scholar] [CrossRef]
  112. Shim, J.H.; Kim, C.I. Measuring Resilience to Natural Hazards: Towards Sustainable Hazard Mitigation. Sustainability 2015, 7, 14153–14185. [Google Scholar] [CrossRef]
  113. Man, S.; Wu, X.; Yang, Y.; Meng, Q. An Assessment Approach to Urban Economic Resilience of the Rust Belt in China. Hindawi Complex. 2021, 2021, 16. [Google Scholar] [CrossRef]
  114. You, X.; Sun, Y.; Liu, J. Evolution and Analysis of Urban Resilience and ifs influencing factors : A case study of Jiangsu Province, China. Nat. Hazards 2022, 113, 1751–1782. [Google Scholar] [CrossRef]
  115. Östh, J.; Reggiani, A.; Nijkamp, P. Resilience and Accessibility of Swedish and Dutch Municipalities. Transportation 2018, 45, 1051–1073. [Google Scholar] [CrossRef]
  116. Wang, H.; Cao, C.; Ma, X.; Ma, Y. Methods for Infectious Disease Risk Assessments in Megacities Using the Urban Resilience Theory. Sustainability 2023, 15, 16271. [Google Scholar] [CrossRef]
  117. Chen, X.; Jiang, S.; Xu, L.; Xu, H.; Guan, N. Resilience Assessment and Obstacle Factor Analysis of Urban Areas Facing Waterlogging Disasters: A Case Study of Shanghai, China. Environ. Sci. Pollut. Res. 2023, 30, 65455–65469. [Google Scholar] [CrossRef]
  118. Ma, F.; Wang, Z.; Sun, Q.; Yuen, K.F.; Zhang, Y.; Xue, H.; Zhao, S. Spatial temporal evolution of urban resilience and its influencing factors: Evidence from the Guanzhong plain urban agglomeration. Sustainability 2020, 12, 2593. [Google Scholar] [CrossRef]
  119. Kim, H.; Son, J.; Lee, S.; Koop, S.; Van Leeuwen, K.; Choi, Y.J.; Park, J. Assessing Urban Water Management Sustainability of a Megacity: Case Study of Seoul, South Korea. Water 2018, 10, 682. [Google Scholar] [CrossRef]
  120. Zhang, C.; Li, Y.; Zhu, X. A Social-Ecological Resilience Assessment and Governance Guide for Urbanization Processes in East China. Sustainability 2016, 8, 11. [Google Scholar] [CrossRef]
  121. Xu, L.; Zhang, Z.; Tan, G.; Zhou, J.; Wang, Y. Analysis on the Evolution and Resilience of Ecological Network Structure in Wuhan Metropolitan Area. Sustainability 2022, 14, 8580. [Google Scholar] [CrossRef]
  122. Karutz, R.; Klassert, C.J.A.; Kabisch, S. On Farmland and Floodplains—Modeling Urban Growth Impacts Based on Global Population Scenarios in Pune, India. Land 2023, 12, 1051. [Google Scholar] [CrossRef]
  123. Otuoze, S.H.; Hunt, D.V.L.; Jefferson, I. Neural Network Approach to Modelling Transport System Resilience for Major Cities: Case Studies of Lagos and Kano (Nigeria). Sustainability 2021, 13, 1371. [Google Scholar] [CrossRef]
  124. Zare, N.; Talebbeydokhti, N. Policies and Governance Impact Maps of Floods on Metropolitan Shiraz (the First Step toward Resilience Mod-elling of the City). Int. J. Disaster Risk Reduct. 2018, 28, 298–317. [Google Scholar] [CrossRef]
  125. Ranjan, N.; Biswas, A.; Neppl, M. Analysing the Institutional Framework for Climate Resilient Metropolitan Regions from the Global North and Global South. Springer Geogr. 2023, 26, 601–623. [Google Scholar]
Figure 1. Article search flow in the study literature review (SLR) process based on the keywords urban resilience in metropolitan or megacity or megacities.
Figure 1. Article search flow in the study literature review (SLR) process based on the keywords urban resilience in metropolitan or megacity or megacities.
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Figure 2. Top 100 keyword terms from articles related to urban resilience in metropolitan areas based on frequency of occurrence. Cluster 1 (red color): 36 terms centered on the keyword “China”; Cluster 2 (green color): 32 terms centered on the keyword “metropolitan area” and Cluster 3 (blue color): 32 terms centered on the keyword “urban area”.
Figure 2. Top 100 keyword terms from articles related to urban resilience in metropolitan areas based on frequency of occurrence. Cluster 1 (red color): 36 terms centered on the keyword “China”; Cluster 2 (green color): 32 terms centered on the keyword “metropolitan area” and Cluster 3 (blue color): 32 terms centered on the keyword “urban area”.
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Figure 3. Top 100 keyword terms from articles related to urban resilience in metropolitan areas based on link frequency and total link strength.
Figure 3. Top 100 keyword terms from articles related to urban resilience in metropolitan areas based on link frequency and total link strength.
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Figure 4. (a) The correlation between published document countries. (bd) Recent positions of the keywords for the country with highest number of published articles related to urban resilience in metropolitan areas or megacities: (b) United States, (c) China and (d) Italy.
Figure 4. (a) The correlation between published document countries. (bd) Recent positions of the keywords for the country with highest number of published articles related to urban resilience in metropolitan areas or megacities: (b) United States, (c) China and (d) Italy.
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Figure 5. Development of urban resilience research in metropolitan areas from year to year.
Figure 5. Development of urban resilience research in metropolitan areas from year to year.
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Figure 6. Percentage of articles based on (a) spatial scale and (b) research approach method.
Figure 6. Percentage of articles based on (a) spatial scale and (b) research approach method.
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Table 1. Dimension categories of urban resilience.
Table 1. Dimension categories of urban resilience.
DimensionDescriptions
SocialThe 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].
EconomicThe 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/environmentThe ability of quality infrastructure and ecosystems to protect, provide and connect communities during times of shock [15].
InstitutionalThe ability of all types of institutions and key actors to continuously adapt to changing conditions, including the ability to respond to negative phenomena [23].
Table 2. Types of shock to urban resilience.
Table 2. Types of shock to urban resilience.
Type of ShocksDescriptionsExample
EconomicDisrupts the supply chain by reducing demand 2008 Financial Crisis, 2020 Economic Crisis
InstitutionalInstituional change that changes the economic landscapeBrexit, COVID-19 policies, North American Free Trade Agreement (NAFTA)
OrganizationalChanges in industrial structure due to foreign competition alter global supply chainsChange in labour laws and consumption preference
EnvironmentalDisrupts the supply chain by halting productionEarthquakes, floods, climate change, forest fires
Man-madeDisrupts the supply chain by halting productionTerrorist attacks
TechnologicalDisruptive technology that changes the economic landscape disrupting global supply changesSteam engine, blockchain technology
EpidemicAlters the economic landscape and disrupts the supply chain by halting productionCOVID-19, severe acute respiratory syndrome (SARS), Ebola pandemics
Source: Ref. [5].
Table 3. Spatial scale categories of urban resilience.
Table 3. Spatial scale categories of urban resilience.
Spatial ScaleResilience Research Focus
GlobalLimitations on disaster reduction and adaptation to climate change.
NationalIn 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.
RegionalFocus 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/IndividualFocus on human capital, physical and mental health in the face of threats.
Source: Ref. [23].
Table 5. Various types of shocks/disaster factors that occur in metropolitan areas on various continents of the world.
Table 5. Various types of shocks/disaster factors that occur in metropolitan areas on various continents of the world.
NoDisaster FactorsType of ShockMetropolitan Asia Metropolitan North AmericaMetropolitan South AmericaMetropolitan EuropeMetropolitan AfricaMetropolitan Australia and New Zealand
1Non-NatureEconomiceconomic 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, deindustrializationeconomic crisis (7), food security, transition economy (3)socio–economic pressures food security, rising oil prices, socio–economic pressures
InstitutionalDecentralizationDecentralization Institutional transformation, city policy, decentralization-
Technologypublic transportation network (3), use of technological devices, infrastructure failure, airport closures, urban rail transit disruption, technological shifts, food availability disruptionpublic transportation use of e-mobile applications, public transportation, automation and advanced technology-Public transport
Medicalresource organization, political instability
2HumansHuman creative/artificialHuman 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 racismLand use changeurban sprawl, congestion, urbanization (3)urbanization (4), child displacement, congestion
3NatureEnvironmentfloods (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, wetlandshurricane, 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 stresssea level rise, climate change (9), energy crisis, volcanic eruptions, ecological change, earthquakes, floods (5), heat waves, environmental service degradationextreme heat (3), natural disasters, floods (3), climate change, drought, sea level riseEarthquakes, loss of biodiversity, environmental stress and ecological degradation
EpidemicCOVID-19 (6), epidemic disaster, infectious diseaseCOVID-19 (2)COVID-19 (2)COVID-19 (9)COVID-19 COVID-19
Description: The number “x” in brackets (x) indicates the number of shock/disaster events.
Table 6. Identified forms of analysis in research methods for urban resilience assessment.
Table 6. Identified forms of analysis in research methods for urban resilience assessment.
Forms of Analysis in Research MethodsSpatial Scale References
  • Qualitative Approach
-
Adaptive and transformative capacity
-
Strategic and policy analysis
-
Institutional framework analysis
-
Community/individual building initiative
-
Resiliency assessment through questionnaire, interview
-
Descriptive analysis of case studies
City
City/Metropolitan
Metropolitan
Community
Regional/National
Case study
[48,49]
[45,50,51]
[52]
[53]
[54,55]
[56]
b.
Quantitative Approach
-
Resiliency or Resistance Index
-
Risk Assessment Index
-
Influencing factors Analysis
-
Spatial Analysis
-
Social Network Analysis
-
Optimization model
-
Simulation model (System Dynamic)
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]
c.
mixed-methods approach
-
Combination of factor analysis and expert opinion
-
Combination of relationship between variables of extreme heat and perception of personal experiences, social culture responses
-
Combination of vulnerability assessments, adaptive capacity, and response strategies
-
Combination of Social Network Analysis and Qualitative
-
(Interview)
City
Communities
Metropolitan
Metropolitan
[73]
[74]
[75]
[76]
Table 7. The relationship of various reviews in evaluating the urban resilience assessment.
Table 7. The relationship of various reviews in evaluating the urban resilience assessment.
Forms of ResilienceUrban System PerformanceUrban System Capacity
ReviewThe 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 methodologyDeterministic (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 MethodBenchmarking or counterfactual, such as resilience index measurement, influencing factors, impact measurement, temporal resilienceCausal mechanisms or policy implications, descriptive analysis of case studies,
Spatial ScaleGenerally in the city, regional and national scale, few in the local scaleGenerally in the local scale, society/community
Dimensions/Issues discussedRegional 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
IndicatorThe 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

AMA Style

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 Style

Saptono, 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 Style

Saptono, 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

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