Sustainable development is a hot topic of global concern and sustainable human settlements (HS) are crucial to people’s happiness. Thus, strengthening the construction of HS will help enrich human settlements geography with theories of HS interactions, clarify the existing problems of the Chengdu-Chongqing urban agglomeration (CC), promote the harmonization of the human-land relationship, and realize the SDGs. The results were as follows. (1) the quality of HS exhibited an upward trend with diminishing disparities in PLE functions. (2) A spatial layout featuring the high quality of HS in the east and west and low quality in the central areas was identified, with Chengdu and Chongqing serving as two high-value core areas. (3) The evolution of the quality of HS levels to achieve a leapfrog shift was challenging and the spatial spillover effect and phenomenon of “club convergence” were evident. (4) Living function was a primary obstacle at the criterion layer and indicators within production function became major obstacle factors at the element layer. These findings have enriched the research scope of human settlements geography from the scale of urban agglomerations, and provided scientific decisions for the SDGs.

This study introduces risk theory of environmental science into human settlement science using 2004–2013 statistics, remote sensing data, and thematic maps. The entropy weight method and risk-index model are both used to study the characteristics of the time course and spatial pattern of human settlement risk in 31 provincial regions in China. In addition, influential mechanisms of vulnerability, functionality, stress, and adaptability on environmental risks are analyzed. Three primary results are obtained. First, for temporal characteristics, environmental risks of human settlements increased significantly from 2003 to 2012. The year 2006 marked both a sudden change and the cut-off point after which human settlements in China experienced qualitative changes and new risks. Second, for spatial characteristics, the risk index of human settlements decreased gradually from the southwestern to the northeastern, northwestern, and northern parts of China. The risk index of human settlement spaces differed significantly, with obvious block aggregation of spatial-distribution characteristics. Third, for relevant factor characteristics, between 2003 and 2012, the temporal change in vulnerability is relatively stable, with a slight increase in functionality and a slight decrease in adaptability. Spatially, Qinghai, Tibet, southwestern China, Guangdong, Guangxi, Beijing, and Tianjin had relatively high vulnerability in human settlements; Beijing, Tianjin, Jiangsu, and Zhejiang had the best functionality; Hunan and Sichuan had relatively high stress; and Guangdong, Jiangsu, and Zhejiang had relatively stronger adaptability. Further consideration and discussion are required on the environmental risks for different social groups and at different geographical scales, as well as on the uncertainty and long-term features of environmental risks in addition to environmental justice issues.

In the information age, the new wave of the information technology revolution has profoundly changed our mode of production and way of life. Pseudo human settlements (PHS), consisting of digits and information, have become increasingly important in human settlements (HS) systems, and become a strong support for the high-quality development of global HS. Against this background, clarifying the spatiotemporal heterogeneity and driving mechanisms of the coupling and coordination between the PHS and real human settlements (RHS) is of great significance to the high-quality development of HS and providing a reasonable explanation of today’s man–land relationship. Therefore, we developed a theoretical framework system for describing PHS–RHS coupling and coordination based on multi-source data such as internet socialization, public utility, and remote sensing images, etc. Taking the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR), which is the key region consolidating China’s “two horizontal and three vertical” urbanization strategy, as a case study area, we have comprehensively analyzed the spatiotemporal heterogeneity of the coupling and coordination of PHS and RHS and its driving mechanism in UAMRYR during the period of 2011–2021, by comprehensively applying the modified coupling coordination degree (CCD) and other models. The results show are as follows: (1) Temporal process—The CCD exhibited a reverse L-shaped increasing trend. The CCD class varied significantly, with the extremely uncoordinated and severely uncoordinated classes present at the beginning of the study period and disappearing toward the end of the study period, while the well coordinated and highly coordinated classes were absent at the beginning of the study period and appeared toward the end of the study period. (2) Spatial pattern—The CCD exhibited an equilateral triangle-shaped, core–margin spatial pattern and a characteristic of core polarization. Overall, the spatial distribution of the CCD exhibited a characteristic of “high in the central region, low in the eastern and western regions, and balanced in the south–north direction”. (3) Dynamic evolution—The CCD increased more rapidly in the north-eastern direction than in the south-western direction; the CCD exhibited north-eastward migration and dispersion, and the spatial variability decreased. (4) Driving mechanisms—The primary factors affecting the CCD varied significantly over time. The living system was dominant in the PHS, whereas the human system was dominant in the RHS. The PHS had a greater effect than the RHS on the CCD. The study broadens the research scope of human settlements geography, establishes a scientific foundation for advancing urban HS construction in the UAMRYR, and offers theoretical support for the high-quality development of cities in the UAMRYR.

The existing research on Beautiful China focuses on the major strategic research that is horizontal and comprehensive, and it is urgent to conduct a vertical and in-depth study from the important focus of human settlements. This paper proposes the theoretical framework of “five-sphere integrated plan”, “three-state entirety”, and “binary fusion” of beautiful human settlements, and integrates the entropy power method, kernel density estimation method, geographic probe, and spatial analysis to study the spatio-temporal Laws and the driving mechanism of beautiful human settlements in Liaoning Province. The results show that: (1) In terms of time course, from 2009 to 2018, the beautiful human settlement in Liaoning showed a fluctuating upward trend, and there were more obvious stage divergence characteristics and discrete characteristics; over time, they clustered from low level to high level. (2) In terms of spatial pattern, beautiful human settlements in general showed regional heterogeneous characteristics. The construction in western Liaoning is relatively stable, while northern Liaoning has changed greatly. There is an obvious inverted “U” spatial structure in the province, and it was both higher in the north and south and lower in the east and west, specifically decreasing from southeast to northwest. The distribution pattern is a “dicaryon” dominated by Shenyang and Dalian, and a “triad” trend of core area, development area, and starting area. (3) System properties, such as environmental, support, and social systems show fluctuating upward trends, while systems such as population show downward trends with different discrete characteristics. (4) Driving mechanisms, social systems, and support systems are the main driving systems, and it is also driven by a combination of urban economic strength, population quantity and quality, infra-structure development such as housing, and emerging technology development. The purpose of studying the beautiful human settlements is to promote the integration and development of the sciences of human settlements and other cross disciplines and to clarify the focus of Liaoning local government on building a Beautiful China.