New-type urbanization and rural revitalization have gradually become national strategies, and are an objective requirement for China to be able to enter into a new era of socialism with Chinese characteristics and also an inevitable result of the integration of new-type urbanization and rural development in the new stage. This paper reviews the classic theories and cognition of the research on urban–rural relations at home and abroad, and outlines the stage evolution characteristics of urban–rural relations in China. It is believed that urban-biased urbanization has widened the development gap between urban and rural areas since reform and opening up. Under the guidance of the two strategies of new-type urbanization and rural revitalization, urban and rural areas have transitioned from “one-way flow” to “bilateral interaction”, and from “urban bias” to “urban–rural integration”. This paper puts forward a research framework and scientific issues regarding the integration of new-type urbanization and rural revitalization from multidisciplinary perspectives. The integration of these two major strategies will contribute to a new situation of the coordinated and high-quality development of urban and rural areas in the new era.

Continued warming trends lead to an increasing risk of exposure to extreme heatwaves, which threaten the health of urban residents, especially the ageing population. Here, we project the spatiotemporal trend of future exposure risk across 9188 global urban settlements between 2020 and 2100 under the shared socioeconomic pathway (SSP) 2-4.5 and SSP5-8.5 scenarios. Results show that urban heatwave exposure risk increases by 619% and 1740% for SSP2-4.5 and SSP5-8.5, respectively, and by 1642% to 5529% for the elderly. Notably, 69% of the elderly exposure risk comes from middle-income countries, where the increasing trend on the regional average is 1.2 times higher than that of high-income countries. There is an increasing trend towards greater concentration on large cities, especially in low- and lower-middle-income countries. In high-income countries, climate effects contribute 39% to 58% of increasing exposure for elderly individuals, whereas ageing effects play more prominent role in lower-income countries. This emphasizes the disproportionately higher heat-related burden for elderly individuals and inequitable trends in lower income countries. Understanding the vulnerable and priority regions in future heatwave exposure will inform adaptation strategies to support urban climate-resilient development.

Global large-scale urbanization has a deep impact on climate change and has brought great challenges to sustainable development, especially in urban agglomerations. At present, there is still a lack of research on the quantitative assessment of the relationship between urban scale and urban expansion and the degree of the urban heat island (UHI) effect, as well as a discussion on mitigation and adaptation of the UHI effect from the perspective of planning. This paper analyzes the regional urbanization process, average surface temperature variation characteristics, surface urban heat island (SUHI), which reflects the intensity of UHI, and the relationship between urban expansion, urban scale, and the UHI in the Beijing–Tianjin–Hebei (BTH) urban agglomeration using multi-source analysis of data from 2000, 2005, 2010, and 2015. The results show that the UHI effect in the study area was significant. The average surface temperature of central areas was the highest, and decreased from central areas to suburbs in the order of central areas > expanding areas > rural residential areas. From the perspective of spatial distribution, in Beijing, the southern part of the study area, the junction of Tianjin, Langfang, and Cangzhou are areas with intense SUHI. The scale and pace of expansion of urban land in Beijing were more than in other cities, the influencing range of SUHI in Beijing increased obviously, and the SUHI of central areas was most intense. The results indicate that due to the larger urban scale of the BTH urban agglomeration, it will face a greater UHI effect. The UHI effect was also more significant in areas of dense distribution in cities within the urban agglomeration. Based on results and existing research, planning suggestions are proposed for central areas with regard to expanding urban areas and suburbs to alleviate the urban heat island effect and improve the resilience of cities to climate change.

Sustainable urban growth is an important issue in urbanization. Existing studies mainly focus on urban growth from the two-dimensional morphology perspective due to limited data. Therefore, this study aimed to construct a framework for estimating long-term time series of building volume by integrating nighttime light data, land use data, and existing building volume data. Indicators of urban horizontal expansion (UHE), urban vertical expansion (UVE), and comprehensive development intensity (CDI) were constructed to describe the spatiotemporal characteristics of the horizontal growth, vertical growth, and comprehensive intensity of the Beijing–Tianjin–Hebei (BTH) urban agglomeration from 2013 to 2023. The UHE and UVE increased from 0.44 and 0.30 to 0.50 and 0.53, respectively, indicating that BTH has simultaneously experienced horizontal growth and vertical growth and the rate of vertical growth was more significant. The UVE in urban areas and suburbs was higher and continuously increasing; in particular, the UVE in the suburbs changed from 0.35 to 0.60, showing the highest rate of increase. The most significant UHE growth was mainly concentrated in rural areas. The spatial pattern of the CDI was stable, showing a declining trend along the urban–suburb–rural gradient, and CDI growth from 2013 to 2023 was mainly concentrated in urban and surrounding areas. In terms of temporal variation, the CDI growth during 2013–2018 was significant, while it slowed after 2018 because economic development had leveled off. Economic scale, UHE, and UVE were the main positive factors. Due to the slowdown of CDI growth and population growth, economic activity intensity, population density, and improvement in the living environment showed a negative impact on CDI change. The results confirm the validity of estimating the multi-dimensional growth of regions using remote sensing data and provide a basis for differentiated spatial growth planning in urban, suburban, and rural areas.