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Economic polarization is a special manifestation of economic disparity which intensifies the gap between the rich and the poor in a region and brings about a series of social problems. Though more and more scholars are studying the phenomenon of economic polarization, there are few studies on polarization level division and early warning analysis in the existing literature. The main purpose of this paper is to propose a standard for rationally dividing the level of economic polarization. This paper firstly analyzes the current situation of economic polarization by using the economic data of 54 counties and cities in Jiangsu Province from 2000 to 2016 and secondly predicts the economic polarization level of Jiangsu Province from 2017 to 2015 through the grey model. We find that, according to the classification criteria of polarization levels, the phenomenon of economic polarization in Jiangsu Province is both not as serious as expected and at a moderate level of alertness. The results of this study can provide important reference value for the coordinated development of Jiangsu Province.

Land urbanization is a comprehensive mapping of the relationship between urban production, life and ecology in urban space and a spatial carrier for promoting the modernization of cities. Based on the remote sensing monitoring data of the land use status of the Yangtze River Delta urban agglomeration collected in 2010 and 2020, the spatial differentiation characteristics and influencing factors of land urbanization in the area were analyzed comprehensively using hot spot analysis, kernel density estimation, the multi-scale geographically weighted regression (MGWR) model and other methods. The results indicated the following: (1) From 2010 to 2020, the average annual growth rate of land urbanization in the Yangtze River Delta urban agglomeration was 0.50%, and nearly 64.28% of the counties had an average annual growth rate that lagged behind the overall growth rate. It exhibited dynamic convergence characteristics. (2) The differentiation pattern of land urbanization in the Yangtze River Delta urban agglomeration was obvious from the southeast to the northwest. The hot spots of land urbanization were consistently concentrated in the southeastern coastal areas and showed a trend of spreading, while the cold spots were concentrated in the northwest of Anhui Province, showing a shrinking trend. (3) Compared with the GWR model and the OLS model, the MGWR model has a better fitting effect and is more suitable for studying the influencing factors of land urbanization. In addition, there were significant spatial differences in the scale and degree of influence of different influencing factors. Analyzing and revealing the spatiotemporal characteristics and driving mechanism of land urbanization in the Yangtze River Delta urban agglomeration has important theoretical value and practical significance for the scientific understanding of new-type urbanization and the implementation of regional integration and rural revitalization strategies.

It is of great practical significance to study the spatial characteristics of carbon emission efficiency, industrial structure, their coupling and coordination relationship for China's green development and industrial structure transformation in the new era. From the perspective of coupling, coordination and space, this paper analyzes and summarizes the spatial characteristics of carbon emission efficiency and industrial structure of 19 cities in three metropolitan areas of Jiangsu Province during 2009–2019 and their coupling and coordination relationship. The carbon emission efficiency in this study is represented by the carbon emission economic efficiency index and carbon emission social efficiency index. The results show that (a) the high-emission centers in the three metropolitan areas developed from “three centers” in 2009 to “five centers” in 2019. The continuous high-energy consumption of the secondary industry and the growth of the economic aggregate of the third industry kept the regional high carbon dioxide emissions. (b) The average value of carbon emission economic efficiency in 19 cities continued to increase, indicating that the contribution rate of the same amount of carbon emissions to economic income gradually increased; the growth range of carbon emission economic efficiency index is greater than that of carbon emission social efficiency index, indicating that carbon emission has a more significant effect on the improvement of regional economic development than on the improvement of public service level and residents’ living quality. (d) The solidification degree of carbon emission efficiency is greater than that of the industrial structure (solidification degree carbon emission social efficiency > carbon emission economic efficiency > industrial structure). The high-grade industrial structure in Xuzhou metropolitan area is closely related to the improvement of carbon emission economic efficiency and carbon emission social efficiency, and both are in moderate antagonism. The rationalizing industrial structure in Nanjing metropolitan area is closely related to the improvement of carbon emission economic efficiency, which is in high coordination run-in. The concentration degree of industrial structure in Suzhou-Wuxi-Changzhou metropolitan area is closely related to the improvement of carbon emission economic efficiency and carbon emission social efficiency, which are in polar coordination coupling and high coordination run-in, respectively. The proposed coupling path of carbon emission efficiency-industrial structure can not only alleviate the dynamic disharmony in different cities but also effectively improve the coupling degree in cities.

Exploring population dynamics and its driving factors has important practical significance for guiding reasonable population distribution. In view of this, this paper systematically analyzes the population dynamics and driving factors in China based on the latest three decennial censuses, using research methods such as the population concentration index, the center of gravity model, relative change in population density and multiple linear regression. The conclusions are as follows: (1) China’s population distribution is uneven, and the trend of polarization in population distribution is increasingly evident. The spatial differences in population growth are shifting from east–west to north–south. Under the influence of the “core–periphery effect”, more people are gathering in a few large cities. (2) The factors affecting population changes have obvious temporal variability: terrain and temperature have an increasing impact on China’s population changes. Temperature in particular has become an important factor in China’s population changes. Population changes are gradually shifting from being driven by a single economic factor to being driven jointly by social and economic factors. (3) The factors affecting population changes also have obvious spatial heterogeneity: temperature affects population changes in both the eastern and central–western regions, while terrain only affects population changes in the central–western regions. Currently, population changes in the economically developed eastern region are more driven by economic factors, while the central–western regions are driven by both economic and social factors. Central cities in the central–western regions are experiencing accelerated population agglomeration, while central cities in the eastern region are losing their ability to attract population agglomeration. The above conclusion basically clarifies the patterns and influencing factors of China’s population changes since the 21st century, which can provide a useful reference for future population development and regional planning.