Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model

Assessing the effects of extreme climate risk on urban ecological resilience in China

The frequent occurrence of extreme weather events has imparted significant pressure on urban ecosystem management. Evaluating the relationship between extreme climate risk (ECR) and urban ecological resilience (UER) is a key issue in achieving the green and sustainable development objectives of cities. This study measures UER in China from 2005 to 2020 using the entropy weight method-TOPSIS method, investigates the relationship between ECR and UER using the dynamic GMM model, and further explores the influencing mechanism. The results suggest that ECR has an inhibiting influence on UER. Additionally, the moderating mechanism investigation demonstrates that environmental regulation can mitigate the threat of ECR to UER to a certain extent, and with the regulation effect based on the government's environmental concern being better than that of the market pollution fee payment. The group test outcomes demonstrate that the discrepancies in regions and marketization lead to certain differences in the relationship between ECR and UER. Additional investigation indicates that ECR has an asymmetric relationship with UER at distinct quantiles. Our findings reflect the subtle associations between ECR and UER as a whole, and will help relevant organizations in formulating more precise and scientific policies to enhance urban ecological resilience.

Digital economy development boosts urban resilience-evidence from China

Focusing on the impact of the digital economy on urban resilience is beneficial to the sustainable development of cities. This paper empirically examines the impact of digital economic development on urban resilience and its mechanisms by measuring urban resilience and the level of urban digital economy with the entropy-weighted TOPSIS method using the data of 252 Chinese cities from 2011 to 2020. The findings show that digital economic development effectively promotes urban resilience at the 1% significance level, and this conclusion remains valid after a series of endogeneity and robustness tests. The channel mechanism suggests that the development of the digital economy can improve urban resilience by optimizing urban distributional effects and promoting the upgrading of urban industrial structures. This paper discusses the nonlinear relationship between the two using the MMQR model and the threshold model. The results show that urban resilience development level is in a higher quartile of cities, and digital economy development has a greater impact on urban resilience improvement. Meanwhile, there are two threshold values for the nonlinear impact of the digital economy on urban resilience, which are 0.026 and 0.082, respectively. Further, the spatial effect between the two is also verified. From the perspective of heterogeneity analysis, the digital economy development of high-class cities, key city clusters, and cities in eastern and western regions has a greater effect on urban resilience. This study can provide ideas and inspiration for countries to enhance urban resilience and promote sustainable urban development through the development of the digital economy.

Urban expansion patterns and their driving forces analysis: a comparison between Chengdu-Chongqing and Middle Reaches of Yangtze River urban agglomerations

Urban agglomerations have emerged as the primary drivers of high-quality economic growth in China. While recent studies have examined the urban expansion patterns of individual cities, a comparative study of the urban expansion patterns of urban agglomerations at two different scales is required for a more comprehensive understanding. Thus, in this study, we conduct a two-scale comparative analysis of urban expansion patterns and their driving factors of the two largest urban agglomerations in western and central China, i.e., Chengdu-Chongqing urban agglomeration (CCUA) and the Middle Reaches of Yangtze River urban agglomerations (MRYRUA) at both the urban agglomeration and city levels. We investigate the urban expansion patterns of CCUA and MRYRUA between 2000 and 2020 using various models, including the urban expansion rate, fractal dimension, modified compactness, and gravity-center method. Then we use multiple linear regression analysis and geographically weighted regression (GWR) to explore the magnitude and geographical differentiation of influences for economic, demographic, industrial structure, environmental conditions, and neighborhood factors on urban expansion patterns. Our findings indicate that CCUA experienced significantly faster urban growth compared to MRYRUA. There is an excessive concentration of resources to megacities within the CCUA, whereas there is a lack of sufficient collaboration among the three provinces within the MRYRUA. Additionally, we identify significant differences in the impacts of driving forces of CCUA and MRYRUA, as well as spatial heterogeneity and regional aggregation in the variation of their strength. Our two-scale comparative study of urban expansion patterns will not only provide essential reference points for CCUA and MRYRUA but also serve as valuable insights for other urban agglomerations in China, enabling them to promote sustainable urban management and foster integrated regional development.

The impact of population agglomeration on ecological resilience: Evidence from China

Due to climate change and human activities, ecological and environmental issues have become increasingly prominent and it is crucial to deeply study the coordinated development between human activities and the ecological environment. Combining panel data from 31 provinces in China spanning from 2011 to 2020, we employed a fixed-effects model, a threshold regression model, and a spatial Durbin model to empirically examine the intricate impacts of population agglomeration on ecological resilience. Our findings indicate that population agglomeration can have an impact on ecological resilience and this impact depends on the combined effects of agglomeration and crowding effects. Also, the impact of population agglomeration on ecological resilience exhibits typical dual-threshold traits due to differences in population size. Furthermore, population agglomeration not only directly impacts the ecological resilience of the local area, but also indirectly affects the ecological resilience of surrounding areas. In conclusion, we have found that population agglomeration does not absolutely impede the development of ecological resilience. On the contrary, to a certain extent, reasonable population agglomeration can even facilitate the progress of ecological resilience.

Potential heterogeneity of urban ecological resilience and urbanization in multiple urban agglomerations from a landscape perspective

Rapid urbanization has reduced the capacity of cities to mitigate and withstand disasters. Strengthening urban ecological resilience (ER) is important for improving urban self-organization. Geographical characteristics and developmental status of different cities lead to a more complex relationship between urbanization and ER. Using the three major urban agglomerations in China, we constructed a new framework for assessing the ER from a landscape and ecological processes perspective, and analyzed the driving heterogeneity of urbanization on ER. The results indicated that the ER of Yangtze River Delta (YRD) and Pearl River Delta (PRD) decreased continuously from 2000 to 2018, while the ER of Beijing-Tianjin-Hebei (BTH) decreased from 2000 to 2010, and then increased from 2010 to 2018. The resilience level of PRD was significantly lower than those of BTH and YRD. The urbanization process had a negative impact on ER, and the contribution of urbanization factors to ER varied significantly across cities, and population factors have the most direct influence. Curve fitting analysis further deepened our understanding of heterogeneity, investigating from the perspective of landscape and driving factors, and suggesting improvement measures. This study can deepen the understanding of the impact of urbanization on resilience and provide scientific guidance for achieving regional sustainability.

Assessment of the Carrying Capacity and Suitability of Spatial Resources and the Environment and Diagnosis of Obstacle Factors in the Yellow River Basin

The assessment of the carrying capacity and suitability of spatial resources and the environment can provide effective guidance for regional planning and make vital contributions to the high-quality advancement of society and the economy. Additionally, this scientific evaluation of the spatial carrying capacity and suitability of urban production-living-ecological space (PLES) has important scientific value as well as practical significance for territorial spatial planning. This paper takes the cities along the Yellow River Basin (YRB) as the research object; establishes the PLES resource and environment carrying capacity evaluation index system; uses the multi-indicator superposition method and entropy weight method to evaluate the ecological importance, production and life carrying capacity of 78 cities in the YRB from 2010 to 2020; obtains the final ecological importance, production and life suitability levels based on the carrying capacity combined with the location conditions; and uses exploratory spatial data analysis (ESDA), the barrier degree model and other methods to determine the cities' spatial and temporal patterns and influencing factors. The findings indicate that: (1) Ecological importance is characterized by "high upstream and low downstream"; the suitability for production is higher mainly in the eastern coastal area; the suitability of life as a whole is increasing, and the higher grade is in some provincial capitals and surrounding cities. (2) The local Moran's I all passed the test, and the relationship between PLES showed a significant positive spatial correlation. The clustering characteristics of ecological importance and production suitability are strong, while the clustering characteristics of suitability for living functions are relatively weak. (3) Biodiversity, significance of water conservation and significance of wind and grit control functions are the main barrier factors affecting the ecological importance of the YRB; industrial value-added output per unit of industrial land, number of industrial enterprises above the scale and GDP per capita are the dominant factors affecting the production suitability of the study area; total water-resource utilization per capita, total sewage treatment per capita and residential land area per capita are the main barrier factors of living suitability.

Can Population Mobility Make Cities More Resilient? Evidence from the Analysis of Baidu Migration Big Data in China

Knowledge spillover and capital agglomeration caused by population migration behavior are of great significance for improving the carrying capacity and adaptability of the urban economy and promoting high-quality economic development. Based on the big data collected on urban migration during the Spring Festival travel period, this paper constructs geographic, economic and geo-economic matrices, introduces two instrumental variables, and uses a spatial econometric model to investigate the mechanism between population mobility and urban economic resilience. The results show that (1) urban economic resilience exhibits spatial correlation, and the correlation order is geo-economic matrix > economic matrix > geography matrix; (2) the economic resilience of inflow areas is significantly affected by the net inflow of population, and the urban economic resilience index increases by 0.36−0.56% when the population mobility index increases by one unit; (3) in the case of economic and geo-economic matrices, there is a spatial interaction relationship of neighbor-companion in the mechanism of population migration on urban economic resilience; and (4) the mechanism is significantly impacted by innovation input and fixed asset investment, with positive moderating effects. In the geographical and economic matrices, the innovation input effect has a negative externality, while in the economic and geo-economic matrices, the fixed asset investment effect has a positive externality.

Multiscale Impact of Environmental and Socio-Economic Factors on Low Physical Fitness among Chinese Adolescents and Regionalized Coping Strategies

As low physical fitness in adolescents increases their risk of all-cause mortality in future adulthood as well as regional public health budgets, many scholars have studied the factors influencing physical fitness in adolescents. However, the spatial non-stationarity and scale between physical fitness and influencing factors in adolescents are often neglected. To rectify this situation, this study constructed a multi-scale geographically weighted regression model based on data from the China National Student Fitness Survey and the China Statistical Yearbook in 2018 to investigate the spatial patterns of factors influencing low physical fitness among adolescents. The results showed that the influencing factors for measuring the physical fitness of Chinese adolescents had significant spatial heterogeneity and multi-scale effects. The local R² values were relatively low in the western region of China. Consideration should be given to increasing the lifestyle and ethnic and cultural characteristics of local residents when selecting influencing factors in the future. The physical fitness of men was mainly influenced by socio-economic factors, while that of women was influenced by natural environmental factors. According to the different spatial distribution patterns of MGWR, this study suggests that each region should develop regionalized strategies to cope with the low physical fitness of adolescents, including taking advantage of the natural environment to develop physical fitness promotion projects, accelerating the upgrading of industrial structures in the north-eastern and western regions, and the need to remain cautious of rapid urbanization in the east.

Spatial-Temporal Evolution and Driving Factors of the Coupling Coordination between Urbanization and Urban Resilience: A Case Study of the 167 Counties in Hebei Province

Urban resilience, as an important ability to deal with disasters in the process of urbanization, has been paid more and more attention as the result of the increasing risks that are caused by rapid urbanization. China is taking the county level as the basic unit to promote new-type urbanization and constructing resilient cities has become one of the development strategies. However, to achieve this strategy researchers need to analyze the interaction between county urbanization and urban resilience and its driving mechanism, which have been paid little attention. Therefore, this paper selected 167 counties in Hebei Province as the investigation subject. Based on the statistical data from 2010 to 2020, a comprehensive index system was developed to quantify the degree of coupling coordination between urbanization and urban resilience, and the spatial Durbin model was used to analyze the driving mechanism of it. The study shows that: Firstly, the urbanization level of counties rose year after year, with there being a geographical distribution that was "lower from southeast to northwest". The level of urban resilience increased year after year, showing a geographical distribution that was "higher from south to north" and a "core-edge" feature that was localized. Secondly, the coupling coordination degree increased steadily, and the overall level changed from a basic imbalance to a mild imbalance. In space, it is bounded by "Pingquan City-Pingshan County", which showed the distribution of "high in the east and low in the west, high in the center and low on the outskirts". Thirdly, the coupling coordination degree has spatial spillover effect. Government financial expenditure, innovation level, industrial upgrading level and urban shape index all influence the coupling coordination degree positively, with a successively decreasing impact, while the urban compactness has significant negative impacts. This study indicates that the regional differences exist in the coupling coordination degree, and the counties in different development stages need to adopt different strategies to promote the coordinated development of urbanized and resilient cities. Inter-regional support is also necessary in this process. Meanwhile, it is necessary for the government to govern various urban elements, especially in terms of their urban form.

Spatial-Temporal Characteristics of Multi-Hazard Resilience in Ecologically Fragile Areas of Southwest China: A Case Study in Aba

Aba's topography, weather, and climate make it prone to landslides, mudslides, and other natural disasters, which limit economic and social growth. Assessing and improving regional resilience is important to mitigate natural disasters and achieve sustainable development. In this paper, the entropy weight method is used to calculate the resilience of Aba under multi-hazard stress from 2010 to 2018 by combining the existing framework with the disaster resilience of the place (DROP) model. Then spatial-temporal characteristics are analyzed based on the coefficient of variation and exploratory spatial data analysis (ESDA). Finally, partial least squares (PLS) regression is used to identify the key influences on disaster resilience. The results show that (1) the disaster resilience in Aba increased from 2010 to 2018 but dropped in 2013 and 2017 due to large-scale disasters. (2) There are temporal and spatial differences in the level of development in each of the Aba counties. From 2010 to 2016, disaster resilience shows a significant positive spatial association and high-high (HH) aggregation in the east and low-low (LL) aggregation in the west. Then the spatial aggregation weakened after 2017. This paper proposes integrating regional development, strengthening the development level building, and emphasizing disaster management for Aba.

Key Influencing Factors and Optimization Strategy of Epidemic Resilience in Urban Communities-A Case Study of Nanjing, China

COVID-19 has posed a significantly severe impact on both people’s lives and the global economic development. Increasing the community epidemic resilience will considerably improve the national public health emergency response capacity from bottom to top. This study identifies the influencing factors of community epidemic resilience through systematic literature review under the 4R framework, then obtains the relationships of influencing factors through Interpretive structural model, and finally assesses the performance of epidemic resilience using PROMETHEE II method through empirical cases in Nanjing, China. The results show that: (1) Eight factors influencing the epidemic resilience of community are identified, and the economic level plays the root role; (2) Community epidemic resilience can be improved from robustness, rapidity, redundancy and resourcefulness aspects; (3) Through the empirical analysis, the epidemic resilience ranking of community can be displayed (Community D > T > S > F); (4) Additionally, the performance and sensitivity analysis of influencing factors in each community can be demonstrated. (5) Finally, four implications are proposed, namely, allocating public resources rationally, significantly increasing the economic level, ensuring the accuracy of information delivery and conducting disaster learning.

Evaluation and Factor Analysis for Urban Resilience: A Case Study of Chengdu–Chongqing Urban Agglomeration

Resilient cities provide a new operating mechanism for sustainable urban development and can effectively reduce urban disaster losses. Urban resilience has become an important research topic, but few scholars focus on the urban resilience of urban agglomerations in western China. Therefore, this paper takes the Chengdu–Chongqing urban agglomeration of China as the study area and aims to evaluate the resilience level of cities in typical regions of western China. This study uses multiple interdisciplinary methods, such as the entropy weight method, Theil index, and geographically and temporally weighted regression, to evaluate the resilience levels of 16 cities in the region and discuss the influencing factors of regional urban resilience. The results show that the urban resilience of cities in the Chengdu–Chongqing urban agglomeration has evolved from a low to high level. Additionally, there are significant spatial differences in urban resilience in the Chengdu–Chongqing urban agglomeration, and the resilience levels of cities in the east and west of the region are relatively high, while the resilience levels of cities in the south and north are relatively low. Further research found that factors such as administrative level, marketization level, industrial structure, population density, urbanization level, and emergency facility level all have a significant positive impact on the improvement of urban resilience, but this impact has spatial and temporal heterogeneity. Based on the above research results, the strategies have been proposed from the perspective of sustainable urban development to provide a new theoretical support and decision-making reference for improving the resilience level of urban agglomerations in western China.

Assessment of Urban Ecological Resilience and Its Influencing Factors: A Case Study of the Beijing-Tianjin-Hebei Urban Agglomeration of China

Climate change and rapid urbanization bring natural and anthropogenetic disturbance to the urban ecosystem, damaging the sustainability and resilience of cities. Evaluation of urban ecological resilience and an investigation of its impact mechanisms are of great importance to sustainable urban management. Therefore, taking the Beijing-Tianjin-Hebei Urban Agglomeration (BTHUA) region in China as a study area, this study builds an evaluation index to assess urban ecological resilience and its spatial patterns with the resilience surrogate of net primary production during 2000–2020. The evaluation index is constructed from two dimensions, including the sensitivity and adaptability of urban ecosystems, to capture the two key mechanisms of resilience, namely resistance and recovery. Resilience-influencing factors including biophysical and socio-economic variables are analyzed with the multiple linear regression model. The results show that during 2000–2020, the spatial pattern of urban ecological resilience in the BTHUA is characterized by high resilience in the northwest and relatively low resilience in the southeast. High resilience areas account for 40% of the whole region, mainly contributed by Zhangjiakou and Chengde city in Hebei Province, which is consistent with the function orientation of the BTH region in its coordinated development. Along with urbanization in this region, ecological resilience decreases with increased population and increases with GDP growth; this indicates that, although population expansion uses resources, causes pollution and reduces vegetation coverage, with economic growth and technological progress, the negative ecological impact could be mitigated, and the coordinated development of social economy and ecological environment could eventually be reached. Our findings are consistent with mainstream theories examining the ecological impact of socio-economic development such as the Environmental Kuznets Curve, Porter Hypothesis, and Ecological Modernization theories, and provide significant references for future urbanization, carbon neutrality, resilience building, and urban ecological management in China.

Investigating into the Coupling and Coordination Relationship between Urban Resilience and Urbanization: A Case Study of Hunan Province, China

In the context of accelerated urbanization, constructing resilient cities is an effective approach to tackling risks, such as extreme weather, and various urban challenges. The coupling and coordinated development of urbanization and urban resilience is a prominent embodiment of urban sustainable development and high-quality development capacity. In this study, Hunan Province, China, which is frequently affected by various disasters, is selected as a representative for examining the coupling and coordination relationship between urban resilience and urbanization level. The panel data are adopted to construct a dual-system evaluation framework integrating urban resilience and urbanization level based on the entropy weight-coefficient of variation (CV)-CRITIC method. The coupling coordination degree of this dual-system evaluation framework is calculated with the coupling model in physics and GM (1, 1) grey prediction model. Additionally, the spatial–temporal evolution characteristics of the coupling coordination degree are investigated and analyzed by ArcGIS and Geoda software. The following are indicated from the results: (1) The resilience of all cities is related to their geographical location and is characterized by a decrease from east to west; in addition, the resilience level of most cities presents a downward trend with time. (2) The urbanization level of most cities develops stably with time, but there is a growing gap in the urbanization level between regions. (3) There is a strong correlation between urban resilience and urbanization level in all cities; the unbalanced coupling and coordinated development emerge, specifically manifested by the polarization phenomenon. Eventually, a circle-difference spatial distribution pattern that starts from the central urban agglomeration and gradually decreases to the periphery is formed. (4) The prediction results of the coupling coordination degree suggest that there is an increasingly distinct polarization trend for the coupling and coordinated development between cities, and it is necessary to pay attention to those cities with a declined predicted value. (5) There is a significant positive spatial autocorrelation and agglomeration effects in the distribution of the coupling coordination degree of all cities, and the correlation is getting stronger with each passing year; the correlation mode is mainly characterized by homogeneity and supplemented by heterogeneity. Finally, several suggestions are proposed in this paper, in an attempt to lead the coordinated development of regions by novel urbanization and thus promote the sustainable development of cities. The methods and insights adopted in this study contribute to investigating the relationship between urban resilience and urbanization in China and other regions worldwide.

Evolution and analysis of urban resilience and its influencing factors: a case study of Jiangsu Province, China

This research uses panel data of cities in Jiangsu from 2009 to 2018 to construct a resilience framework that measures the level of urban resilience. A combination of the entropy method, Theil index, Moran ' sI , and the Spatial Durbin Model (SDM) is used to explore regional resilience development differences, the spatial correlation characteristics of urban resilience, and its influencing factors. The study finds that: (1) The spatial heterogeneity of regional resilience development is significant, as the overall level of resilience presents a spatial distribution pattern of descending from southern Jiangsu to central Jiangsu and to northern Jiangsu. (2) The total Theil index shows a wave-like downward trend during the study period. The differences between southern Jiangsu, central Jiangsu, and northern Jiangsu make up the main reason for the overall difference of urban resilience in Jiangsu Province. Among the three regions, the gap in resilience development level within southern Jiangsu is the largest. (3) There is a clear positive spatial correlation between urban resilience in the province and an obvious agglomeration trend of urban resilience levels. Among all subsystems, urban ecological resilience is the weakest and needs to be further improved. (4) Lastly, among the five factors affecting urban resilience, general public fiscal expenditure/GDP, which characterizes government factors, has the largest positive impact on urban resilience, while foreign trade has a negative impact. In the following studies, the theme of urban resilience should be constantly deepened, and more extensive data monitoring should be carried out for the urban system to improve the diversity of data sources, so as to assess urban resilience more accurately.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11069-022-05368-x.

Spatial Transformation Characteristics and Conflict Measurement of Production-Living-Ecology: Evidence from Urban Agglomeration of China

The land development by human beings has changed from the initial small-scale and low-level transformation to the comprehensive utilization of large-scale and high-intensity implementations. The contradiction between production-living-ecology space (PLES) has become increasingly prominent while drawing land dividends. As one of the important birthplaces of Chinese civilization and the ecological barrier in the northern region, the rapid urbanization and industrialization of the Yellow River Basin (YRB) make the ecological environment very fragile, and the imbalance of land and space development is extremely serious. Therefore, according to the multifunctional characteristics of land use, this paper establishes a classification system of production space (PS), living space (LS) and ecology space (ES), and discusses the spatiotemporal evolution and conflict distribution characteristics of the PLES with the help of the transfer matrix and spatial conflict index (SCI). The results are as follows. In 1990–2020, agricultural production space (APS), grassland ecology space (GES) and other ecology space (OES) yielded the largest proportion of PLES in the YRB. However, compared with 1990, the area of these spatial types decreased in 2020, while the urban living space (ULS) expanded rapidly. The distribution pattern of PLES was generally consistent, and the transformation between PLES in Ningxia, central Inner Mongolia, Loess Plateau and downstream areas was relatively intense. The conflict index of PLES showed an upward trend, but it was generally in a controllable range. The stable and controllable areas were concentrated in the upstream of the urban agglomeration, and the midstream and downstream were basic out of control and seriously out of control, respectively.

Resilience of Urban Network Structure in China: The Perspective of Disruption

In light of the long-term pressure and short-term impact of economic and technological globalization, regional and urban resilience has become an important issue in research. As a new organizational form of regional urban systems, the resilience of urban networks generated by flow space has emerged as a popular subject of research. By gathering 2017 data from the Baidu search index, the Tencent location service, and social statistics, this study constructs information, transportation, and economic networks among 344 cities in China to analyze the spatial patterns of urban networks and explore their structural characteristics from the perspectives of hierarchy and assortativity. Transmissibility and diversity were used to represent the resilience of the network structure in interruption scenarios (node failure and maximum load attack). The results show the following: The information, transportation, and economic networks of cities at the prefecture level and higher in China exhibit a dense pattern of spatial distribution in the east and a sparse pattern in the west; however, there are significant differences in terms of hierarchy and assortativity. The order of resilience of network transmissibility and diversity from strong to weak was information, economic, transportation. Transmissibility and diversity had nearly identical scores in response to the interruption of urban nodes. Moreover, a highly heterogeneous network was more likely to cause shocks to the network structure, owing to its cross-regional urban links in case of disturbance. We identified 12 dominant nodes and 93 vulnerable nodes that can help accurately determine the impetus behind network structure resilience. The capacity of regions for resistance and recovery can be improved by strengthening the construction of emergency systems and risk prevention mechanisms.

Identification of the Key Influencing Factors of Urban Rail Transit Station Resilience against Disasters Caused by Rainstorms

Improving the ability of the urban rail transit system to cope with rainstorm disasters is of great significance to ensure the safe travel of residents. In this study, a model of the hierarchical relationship of the influencing factors is constructed from the resilience perspective, in order to research the action mechanisms of the influencing factors of urban rail transit stations susceptible to rainstorm disaster. Firstly, the concept of resilience and the three attributes (resistance, recovery, and adaptability) are interpreted. Based on the relevant literature, 20 influencing factors are discerned from the 3 attributes of the resilience of urban rail transit stations. Subsequently, an interpretative structural model (ISM) is utilised to analyse the hierarchical relationship among the influencing factors. The key influencing factors of station resilience are screened out using social network analysis (SNA). Combined with ISM and SNA for analysis, the result shows that the key influencing factors are: “Flood prevention monitoring capability”; “Water blocking capacity”; “Flood prevention capital investment”; “Personnel cooperation ability”; “Emergency plan for flood prevention”; “Flood prevention training and drill”; “Publicity and education of flood prevention knowledge”; and “Regional economic development level”. Therefore, according to the critical influencing factors and the action path of the resilience influencing factors, station managers can carry out corresponding flood control work, providing a reference for enhancing the resilience of urban rail transit stations.

Temporal and Spatial Differentiation in Urban Resilience and Its Influencing Factors in Henan Province

Building resilient cities is playing an increasingly important role in enhancing urban safety and promoting sustainable urban development. However, few scholars pay attention to urban resilience in inland provinces. Choosing Henan Province, as it is a typical representative of China’s major inland economic provinces, has practical guiding significance. This study aims to provide a systematic indicator system and evaluation tool to measure the cuity’s resilience level. Therefore, based on a multidimensional perspective, this paper dissects the urban resilience spatial and temporal evolution characteristics of 18 Henan Province cities with the entropy method, Thiel index, and ESDA (Exploratory Spatial Data Analysis) and explores influencing factors with a spatial econometric model. The main results are as follows: (1) the overall resilience in Henan Province continuously grows, and the resilience level of the Zhengzhou metropolitan area is the highest. In the urban resilience subsystem, economic and social resilience notably drive urban resilience improvement in Henan Province. (2) The spatial difference of urban resilience has been significantly reduced, but the inner metropolitan area presents the characteristics of “core–periphery”. Urban resilience presents a positive spatial correlation, and local spatial agglomeration is relatively stable. (3) Under the state of spatial interaction, urbanization rate, administrative, innovation, market, and industrial structure factors all have significant direct effects and spatial spillover effects on overall resilience, but openness exerts downward pressure on local resilience. (4) On this basis, strategies have been proposed to continuously promote the development of new urbanization, improve the regional coordinated development mechanism, increase market activity, optimize the environment for scientific and educational innovation, and promote the optimization and upgrading of industrial structure. The approach taken in this research may also be useful for developing urban resilience assessment tools in other central plains cities as well as in other cities in the interior of the world with similar conditions.

Study on the Spatiotemporal Evolution and Influencing Factors of Urban Resilience in the Yellow River Basin

The outbreak of COVID-19 has prompted consideration of the importance of urban resilience. Based on a multidimensional perspective, the authors of this paper established a comprehensive evaluation indicator system for evaluating urban resilience in the Yellow River basin (YRB), and various methods such as the entropy value method, Theil index, exploratory spatial data analysis (ESDA) model, and geographical detector model were used to measure the spatiotemporal characteristics and influencing factors of urban resilience in the YRB from 2011 to 2018. The results are as follows. (1) From 2011 to 2018, the urban resilience index (URI) of the YRB showed a "V"-shaped dynamic evolution in the time series, and the URI increased by 13.4% overall. The resilience of each subsystem showed the following hierarchical structure: economic resilience > social resilience > ecological resilience > infrastructure resilience. (2) The URI of the three major regions-upstream, midstream, and downstream-increased, and the resilience of each subsystem in the region showed obvious regional characteristics. The comprehensive difference in URI values within the basin was found to be shrinking, and intraregional differences have contributed most to the comprehensive difference. (3) There were obvious zonal differences in the URI from 2011 to 2018. Shandong Peninsula and Hohhot-Baotou-Ordos showed a "High-High" agglomeration, while the southern and southwestern regions showed a "Low-Low" agglomeration. (4) Among the humanist and social factors, economic, fiscal, market, urbanization, openness, and innovation were found to be the factors that exert a high impact on the URI, while the impacts of natural factors were found to be low. The impact of the interaction of each factor is greater than that of a single factor.

Modelling Voluntary General Population Vaccination Strategies during COVID-19 Outbreak: Influence of Disease Prevalence

A novel statistical model based on a two-layer, contact and information, graph is suggested in order to study the influence of disease prevalence on voluntary general population vaccination during the COVID-19 outbreak. Details about the structure and number of susceptible, infectious, and recovered/vaccinated individuals from the contact layer are simultaneously transferred to the information layer. The ever-growing wealth of information that is becoming available about the COVID virus was modelled at each individual level by a simplified proxy predictor of the amount of disease spread. Each informed individual, a node in a heterogeneous graph, makes a decision about vaccination “motivated” by their benefit. The obtained results showed that disease information type, global or local, has a significant impact on an individual vaccination decision. A number of different scenarios were investigated. The scenarios showed that in the case of the stronger impact of globally broadcasted disease information, individuals tend to vaccinate in larger numbers at the same time when the infection has already spread within the population. If individuals make vaccination decisions based on locally available information, the vaccination rate is uniformly spread during infection outbreak duration. Prioritising elderly population vaccination leads to an increased number of infected cases and a higher reduction in mortality. The developed model accuracy allows the precise targeting of vaccination order depending on the individuals’ number of social contacts. Precisely targeted vaccination, combined with pre-existing immunity, and public health measures can limit the infection to isolated hotspots inside the population, as well as significantly delay and lower the infection peak.

Evaluation of Community Resilience in Rural China-Taking Licheng Subdistrict, Guangzhou as an Example

Resilience of rural communities is becoming increasingly important to contemporary society. In this study we used a quantitative method to measure the resilience regulating ability of rural communities close to urban areas-in Licheng Subdistrict, Guangzhou City, China. The main results are as follows: (1) Rural systems close to urban areas display superior adapting and learning abilities and have a stronger overall resilience strength, the spatial distribution of which is characterized by dispersion in whole and aggregation in part; (2) the resilience of most rural economic subsystems can reach moderate or higher levels with apparent spatial agglomeration, whilst the ecological subsystem resilience and social resilience are generally weaker; the spatial distribution of the former shows a greater regional difference while the latter is in a layered layout; (3) some strategies such as rebuilding a stable ecological pattern, making use of urban resources and cultivating rural subjectivity are proposed on this basis, in order to promote the sustainable development of rural areas and realize rural revitalization. This work also gives suggestion for the creation of appropriate and effective resilience standards specifically targeted for rural community-aiming to achieve the delivery of local sustainability goals.