With social and economic environment changes occurring in the world and deepening of the urbanization process, China’s urban development exhibits a new phenomenon of growth and shrinkage fluctuations. The resource-based city shrinkage phenomenon is particularly prominent. Research on the commonalities and patterns of similar groups should be enhanced. We constructed an urban shrinkage evaluation index system from the three dimensions of population, economy and space. Accordingly, we explored the spatiotemporal evolution characteristics of 175 resource-based cities in China from a multidimensional perspective with the entropy method, shrinkage model and transfer matrix method. The results indicated that most resource-based cities in China occurred in the non-shrinking state, but their development speed gradually decreased or even presented stagflation. The shrinkage measure-related results in the different dimensions revealed that the number of shrinking cities is increasing. The population, economic and comprehensive shrinkage levels were mainly slight and remained stable. The number of cities experiencing moderate and severe shrinkage was relatively small and mostly encompassed short-term shrinkage. Spatial shrinkage demonstrated a clear administrative hierarchy difference. Moreover, the spatial distribution range of shrinking cities in each dimension expanded and exhibited obviously similar characteristics, i.e., shrinking cities were relatively concentrated in Northeast China, while they were more scattered in other regions. Furthermore, the geodetector technique was applied to reveal the influencing factors of resource-based city growth and shrinkage. Based on the results, the change in the secondary industry output value share at the start of the study was the primary factor. The impact of each employment structure indicator from 2014 to 2018 was particularly significant. Comprehensive exploration of the shrinkage characteristics of this particular group of cities and their development behavior from a multidimensional perspective can provide an important reference for the transformation and high-quality development of resource-based cities.

Regional resilience refers to the resilience of a country or region against the ecological environment, social economy, and other internal and external natural factors and human factors in the process of development. When this resilience is lower than a certain critical threshold, the country or region will be in a fragile state. The comprehensive embodiment of ecological resilience, social resilience, and economic resilience of a country or region is regional resilience. Due to the wide range of countries along “the Belt and Road”, differences in natural background conditions and stages of economic and social development among different countries lead to different degrees of vulnerability, and the improvement of resilience is conducive to reducing vulnerability. At the same time, the research on the measurement and differentiation characteristics of regional resilience is of considerable significance to solve the weak foundation of environmental management and the lack of ability to deal with climate change of “the Belt and Road” countries. In this study, by using entropy weighting method and multi-index comprehensive evaluation method, 24 specific indicators are selected from three different dimensions: ecology, economy, and society, to construct a comprehensive evaluation index system about “the Belt and Road” countries resilience, and to evaluate the comprehensive resilience and spatial heterogeneity characteristics of China and 64 countries along “the Belt and Road”, and use multiple linear regression analysis to identify the main influencing factors of comprehensive resilience and analyze its influencing mechanism. According to the research, the overall resilience level of “the Belt and Road” countries shows prominent differentiation characteristics of “extreme difference”, the countries with low and low recovery status account for the vast majority; and the spatial differentiation characteristics of the levels of ecological resilience, economic resilience, and social resilience of countries along “the Belt and Road” are quite different. In countries with high levels of economic development, their comprehensive resilience is significantly higher than that of countries with low levels of economic development. There is no inevitable connection between a country’s economic growth rate and its comprehensive resilience level. At the same time, the relationship between resource richness and comprehensive resilience of countries is not apparent, but for those countries that are over-dependent on resources, the level of resilience is generally below. There is a certain degree of correspondence between urbanization rate and comprehensive resilience, that is, the comprehensive resilience will increase with the increase of urbanization rate. When the urbanization rate rises to a certain level, the level of comprehensive resilience does not change much. In this study, it provides scientific guidance for enriching regional resilience and national sustainable development theory, solving the fragile ecological environment foundation of “the Belt and Road” countries, speeding up the transformation of economic growth mode and dealing with a series of social problems.

The phenomenon of urban shrinkage has spread across the world as the political and economic landscape changes worldwide. The urban development in China has entered a post-development era characterized by coexisting urban expansion and local shrinkage whilst urbanization continues to progress in this country. This paper investigates the urban shrinkage of 80 cities in the Yellow River, China from the perspective of population and economy, based on urban shrinkage models drawing from western countries. It also analyzes the spatiotemporal evolution and influencing factors of urban shrinkage in this area using a spatial panel data model. The results show the following. (1) The phenomenon of urban shrinkage in the Yellow River Basin has gradually occurred and the degree of shrinkage has aggravated. (2) The shrinking cities in the Yellow River Basin are mainly population-related and potential. (3) The phenomenon of urban shrinkage in the Yellow River Basin shows significant spatiotemporal differences. Shrinking cities are mainly distributed in the upper and middle reaches of the Yellow River Basin and the number of shrinking cities has gradually increased over time. (4) In terms of influencing factors, financial, traffic, and medical conditions have a greater impact on population-related and economy-related shrinkage in these cities.

The three northeast provinces are typical areas of regional shrinkage in China. A scientific understanding of their shrinkage and driving mechanism is conducive to the transformation and development of traditional industrial bases in China. This study analyzed the spatiotemporal evolution and driving mechanism of regional shrinkage at the county scale in the three provinces. The main findings are as follows: (1) 40.86% of counties in the three provinces shrank, forming three concentrated shrinking regions. However, comprehensively shrinking regions were narrowed and lessened with the introduction of the Northeast Area Revitalization Plan. (2) The population-related shrinking regions accounted for more than 90% and continued to expand. Such shrinkage was higher in the north than in the south. The degree of economy-related shrinkage was the most serious, and the hotspots were mainly concentrated in Liaoning Province. The scope of space-related shrinkage was most minor, and such shrinkage was relatively mild. (3) When it came to influencing factors, the shrinkage index was positively correlated with the proportion of the secondary industry, the output value of agriculture, forestry, animal husbandry and fishery, the number of industrial enterprises above the designated size, fiscal expenditure, and the balance of resident deposits, and negatively correlated with the altitude, the proportion of the tertiary industry, and population aging. Geographically weighted regression (GWR) and ordinary least squares (OLS) produced similar regression results. The spatial pattern of influencing factors was consistent with the hotspot areas of population-related shrinkage or economy-related shrinkage, with significant spatial differences.