Under the background of promoting more balanced and fuller regional development in the new era, standing at the strategic height of national regional coordinated and balanced development, it is necessary to comprehensively consider the natural environment, the unbalanced situation of economic and social development and the reality of widening gap on both sides of the Hu Huanyong Line, and put forward the basic idea of the Hu Huanyong Line to achieve micro-breakthrough along the Bole-Taipei Line. The Hu Huanyong Line is an important dividing line of population geography, natural geography and ecological environment in China, the dividing line of national main function area and national ecological function area, the dividing line of new urbanization main area and non-main area in China, and the dividing line of unbalanced and inadequate economic and social development in China. In the past 40 years, the gap of economic and social development between the two sides of the Hu Huanyong Line has been widening at an accelerating speed. In the next 30 years, the gap can be narrowed to achieve micro-breakthroughs, focusing on achieving "ten 10%", namely, the proportion of population in the northwest half of China will be 10%, the proportion of total economy will be 10%, with the economic growth rate being more than 10%, the proportion of fixed asset investment in the whole society will be more than 10%, the proportion of local fiscal revenue will be more than 10%, the proportion of actual use of foreign capital will be 10%, the growth rate of per capita GDP will be more than 10%, the rate of increase in the absolute difference in the per capita disposable income of urban residents will be controlled within 10%, the rate of increase in the absolute difference in the per capita disposable income of rural residents will be controlled within 10%, and the absolute gap in education resources will be narrowing at an average annual rate of 10%. In order to achieve the strategic goal of micro-breakthrough, this paper puts forward the main paths and countermeasures to narrow the development gap between the east and the west of the Hu Huanyong Line and attain the micro-breakthrough from the aspects of population micro-layout, economic micro-layout, urbanization micro-layout, industrial micro-layout, moderate water diversion nearby, improvement of ecological compensation and transfer mechanism, construction of the Bole-Taipei Line and implementation of the strategy of further development in the western region.

The extension and penetration of digital technology into rural areas profoundly affects the organization and structure of rural economy, society and politics, and promotes the transformation and reorganization of rural territorial system from the perspective of urban-rural development network. Based on defining the concept of rural digitalization, this paper discusses the coupling relationship between rural digitalization and rural spatial transformation, deeply analyzes the mechanism of rural digitalization and rural spatial transformation, and builds a research framework for rural digitalization development and transformation. The main conclusions are as follows: (1) Rural digitalization is a process of reshaping the physical environment, economic form, social network and spatial organization of rural areas with the wide application of digital technology in vast rural areas. It promotes the digital transformation of rural economic and social forms and spatial organizational structure, including the process, role and effect of digital technology on rural regional space. (2) Under the background of rural digitalization, the transformation of rural space tends to be comprehensive and complex, and multiple spaces such as material, economy, society and culture are superimposed and transformed, and cyberspace and network culture forms are derived under the connection of digital information. (3) The multi-dimensional embedded mechanism of rural digitalization and rural spatial transformation includes the logic of digital infrastructure construction and rural physical environment transformation, the mechanism of digital economic development and rural economic transformation, the relationship between digital technology application and rural social network restructuring, digital governance models and the role of rural spatial organization reconstruction. (4) Under the major strategic direction of urban-rural integrated development and rural revitalization, future research needs to explore frontier fields and innovative dimensions of rural development based on digitalization for strengthening disciplinary contributions. It includes focusing on smart rural application scenarios, developing rural planning and construction systems and engineering technical specifications, and serving the rural sustainable development, informatization and modernization of rural development.

Rational configuration and spatial equity of urban medical facilities is an important topic in geography. The Maximal Accessibility Equality (MAE) model is an important progress in the field of spatial equity-oriented location-allocation models. However, existing studies have paid less attention to the spatial equity measures in MAE models. Aiming to fill this research gap, this study attempts to clarify the meaning of spatial equity of medical accessibility. Based on a review of existing studies, 10 spatial equity measures are selected for investigation in this study. The MAE mode is extended by incorporating these measures. Using medical facilities in Shenzhen as a case study, these improved models are applied, evaluated and compared. The following findings are drawn: (1) From the perspective of theoretical foundation behind the measures, the Coefficient of Variation (CV), Gini coefficient, Mean Absolute Deviation (MAD) and Palma ratio are appropriate for public service spatial equity studies. (2) Based on the performance of models, the improved MAE models incorporating Variance, Standard Deviation, CV, Palma ratio, MAD and Theil index are advantageous. (3) Overall, three measures, including CV, MAD and Palma ratio, are suggested for measuring and optimizing the spatial equity of medical services. Improved MAE models adopting these three measures as objective functions can significantly improve the spatial equity of accessibility to medical services. This study contributes to the literature by improving the spatial equity-oriented location-allocation models. It can provide scientific methods for the spatial planning of public service facilities.

Dynamic community with life cycle is a collection of geographical entities in spatial interaction networks. They connect closely through human movement compared with other spatial entities. However, there is still a lack of systematic approaches for analyzing spatio-temporal variation. In this regard, this paper first constructs the spatio-temporal interaction multilayer network (STIMN) based on human mobility data. Secondly, we extract dynamic communities of STIMN, which reveal the uneven distribution of urban resources and the regularity and diversity of human movement. Thirdly, based on the theories of landscape ecology, we propose a dynamic community evolution model and analyze the clustering patterns, forming the framework of "the community detection - dynamic evolution - clustering analysis". Finally, we apply the framework in the third-ring core area within Wuhan, which shows that: (1) Communities extracted from public activities have similarities and differences with the existing administrative divisions of Wuhan City, which can better reflect the people-oriented urban dynamic spatial organization; (2) Community evolution shows an apparent life cycle of "occurrence - expansion - stability - contraction - disappearance"; (3) The life cycle of different communities is different. Through clustering, communities can be divided into short-term, medium-term and long-term communities. Each type of community has one or more dynamic patterns, such as stability, saddle-shaped and wave-shaped pattern, which are significant to dynamic urban planning and management. This study breaks the limitations of traditional community analysis methods, helps explore the dynamic characteristics of the STIMN and deepens the understanding of the dynamic man-land interaction.

Urban scaling law quantifies the disproportional growth of urban indicators with urban population size, which is one of the simple rules behind the complex urban system. Infectious diseases are closely related to social interactions that intensify in large cities, resulting in a faster speed of transmission in large cities. However, how this scaling relationship varies in an evolving pandemic is rarely investigated and remains unclear. Here, taking the COVID-19 epidemic in the United States as an example, we collected daily added cases and deaths from January 2020 to June 2022 in more than three thousand counties to explore the scaling law of COVID-19 cases and city size and its evolution over time. Results show that COVID-19 cases super-linearly scaled with population size, which means cases increased faster than population size from a small city to a large city, resulting in a higher morbidity rate of COVID-19 in large cities. Temporally, the scaling exponent that reflects the scaling relationship stabilized at around 1.25 after a fast increase from less than one. The scaling exponent gradually decreased until it was close to one. In comparison, deaths caused by the epidemic did not show a super-linear scaling relationship with population size, which revealed that the fatality rate of COVID-19 in large cities was not higher than that in small or medium-sized cities. The scaling exponent of COVID-19 deaths shared a similar trend with that of COVID-19 cases but with a lag in time. We further estimated scaling exponents in each wave of the epidemic, respectively, which experienced the common evolution process of first rising, then stabilizing, and then decreasing. We also analyzed the evolution of scaling exponents over time from regional and provincial perspectives. The northeast, where New York State is located, had the highest scaling exponent, and the scaling exponent of COVID-19 deaths was higher than that of COVID-19 cases, which indicates that large cities in this region were more prominently affected by the epidemic. This study reveals the size effect of infectious diseases based on the urban scaling law, and the evolution process of scaling exponents over time also promotes the understanding of the urban scaling law. The mechanism behind temporal variations of scaling exponents is worthy of further exploration.