A healthy ecosystem is fundamental for sustainable urban development. Rapid urbanization has altered landscape patterns and ecological functions, resulting in disturbances to ecosystem health. Exploring the effects of urbanization on ecosystem health and the spatial relationships between them is significant for cities along the “Belt and Road” aiming to achieve sustainable regional development. This study took the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as an example and measured the urbanization level (UL) and ecosystem health index (EHI) from 2000 to 2020 using multisource data. We used bivariate spatial autocorrelation, the geographically weighted regression model (GWR), and the optimal parameters-based geographical detector (OPGD) model to clarify the impact of urbanization on ecosystem health and the spatial relationship between them from multiple perspectives. The major findings of this study were: (1) the EHI in the GBA decreased significantly during the study period, dropping from 0.282 to 0.255, whereas the UL increased significantly, exhibiting opposite spatial distribution features; (2) there was a significant negative spatial correlation between UL and the EHI and significant spatial heterogeneity between high–low and low–high types in the GBA; (3) the negative effects of urbanization on ecosystem health were predominant and becoming more pronounced in the central GBA. Moreover, urbanization had an increasingly significant negative effect, leading to the deterioration of ecosystem health, in the central GBA. Population urbanization drove land urbanization, which became the main factor affecting ecosystem health in the GBA. Overall, urbanization had a significant negative effect on ecosystem health, with this impact being particularly prominent in the core urban junctions of the GBA, which require urgent attention. The results of the study provide a basis for decision making in the context of the steady urbanization and ecosystem health protection of cities along the “Belt and Road”.

Land use changes induced by human activities change landscape patterns and ecological processes, threatening regional and global ecosystems. Terrain gradient and anthropogenic multi-policy regulation can have a pronounced effect on landscape components. Forecasting the changing trend of landscape ecological risk (LER) is important for national ecological security and regional sustainability. The present study assessed changes in LER in the Sichuan-Yunnan Ecological Barrier over a 20-year period using land use data from 2000, 2010, and 2020. The enhanced Markov-PLUS (patch-generating land use simulation) model was used to predict and analyze the spatial distribution pattern of LER under the following three scenarios. These were business-as-usual (BAU), urban development and construction (UDC), and ecological development priority (EDP) in 2030. The influence of terrain conditions on LER was also explored. The results showed that over the past 20 years, the LER index increased and then decreased and was dominated by medium and low risk, accounting for more than 70% of the total risk-rated area. The highest and higher risk areas for the three future scenarios have increased in spatial extent. The UDC scenario showed the largest increase of 3341.13 km² and 2684.85 km², respectively. The highest-risk level has a strong selectivity for low gradients, with high-level risks more likely to occur at low gradients. The response of ecological risk to gradient changes shows a positive correlation distribution for high-gradient areas and a negative correlation distribution for low-gradient areas. The influence of future topographic gradient changes on LER remains significant. The value of multiscale geographically weighted regression (MGWR) for identifying the spatial heterogeneity of terrain gradient and LER is highlighted. It can play an important role in the formulation of scientific solutions for LER prevention and of an ecological conservation policy for mountainous areas with complex terrain.

With the acceleration of urbanization and profound socioeconomic changes, the influx of people from various social strata into cities has led to the phenomenon of residential segregation. Currently, the international community has accumulated profound theoretical foundations and rich practical experiences in the study of residential segregation. This research, primarily based on the WOS literature database, sorts and summarizes relevant studies on residential segregation in recent years (focusing on publications from 2020 to 2024), emphasizing the following four key aspects: (1) tracing the evolution of the theory of residential segregation and analytical methods; (2) analyzing the main characteristics of urban residential segregation; (3) exploring the driving mechanisms and effects of urban residential segregation; and (4) summarizing research trends and providing future perspectives. This study aids urban planners in more accurately identifying areas and characteristics of residential segregation, optimizing urban layouts, and providing richer and more in-depth theoretical support and practical guidance for the field of urban planning science.

As an important ecological ecotone of water and land ecosystems, the lakeside is characterized by a variety ecosystem services and high vulnerability. Forest land is important in resolving the ecological risks of the lakeside area and building its ecological base. It is important to explore the effect of change in forest land on landscape ecological risk in the lakeside area, alleviate the contradiction between ecological protection and construction and development in the area, and realize sustainable development. The present study attempted to explore the spatial and temporal evolutionary features of forest land in the Erhai rim region from 2000 to 2020 using bivariate spatial autocorrelation and multi-scale geographical weighted regression (MGWR) models. The following are the findings of this investigation of the 2000–2020 period: (1) the forest land area in the region generally decreased, first increasing and then decreasing, and was mainly occupied by cultivated land and artificial surfaces; (2) the total landscape ecological risk in the region presented an upward trend, and medium- and higher-risk areas were the main risk areas, with the latter increasing; (3) the impact of forest land expansion and contraction intensity on landscape ecological risk exhibited spatial and temporal heterogeneity. The main forms of forest land change at different stages differed, and the impacts on landscape ecological risk were also different. Reasonable forest land expansion can effectively alleviate the growth in landscape ecological risk, whereas the shrinkage of forest land would aggravate the landscape ecological risk in the Erhai rim region. Moreover, the findings can offer reference for the exploration of ecological protection and coordinated optimization of economic development in Erhai Lake.

Rural livelihood resilience (RLR) is significant for the sustainability of rural areas, farmers and agriculture. This research takes the mountainous areas of Southwest China as the study areas and integrates the buffer, adjustment and renewal capabilities to construct a RLR analysis framework and evaluation indicator system. The RLR of 234 sample counties was evaluated using set pair analysis, and the influencing factors of RLR were investigated using Geodetector. The aim is to scientifically analyze the vertical spatial differentiation and influencing factors of RLR and fully explore the risk-resistant potential of rural livelihood systems in mountainous areas. The results show that (1) From 2000 to 2020, RLR increases significantly, but the level is still low, and its structure shows a primary pattern of “buffer capability > adjustment capability > renewal capability”. (2) There is no significant negative correlation between RLR and terrain gradients, especially in the middle and low mountains. RLR in high mountainous areas is significantly lower than in low and medium mountainous areas, but the gap is narrowing. There are no significant gaps in RLR and various capabilities between low and medium mountain areas. (3) Economic development, non-agricultural industries and grassroots autonomous organizations are essential determinants for RLR. Economic development, grassroots autonomous organizations and transportation conditions are more important in low and medium mountain areas, while non-agricultural industries and medical conditions contribute more to high mountainous areas. (4) To enhance the RLR, policy recommendations should place a strong emphasis on extending the agricultural industry chain, improving rural production and living infrastructure and strengthening the supply of high-quality social public services. The findings can provide a scientific basis for governments to implement rural revitalization strategies and improve farmers’ well-being, as well as practical guidance for enhancing the risk resistance ability of underdeveloped mountainous rural areas.

The evaluation of housing conditions is a crucial aspect of determining the well-being of residents and the sustainable development of settlements. Assessing housing conditions at a macro-level is imperative to understand the differences in well-being and livability among residents in various regions within a country. Unfortunately, the spatial variation characteristics of housing conditions in China have not been extensively studied at the county scale. Thus, this study examines the housing conditions in China by using 2846 counties as the basic research unit. A housing condition evaluation index system, comprising seven indicators, is constructed based on three aspects: housing spaciousness, internal facilities, and elevator configuration. The entropy value method is used to determine the weights of the indicators, and the spatial difference patterns and spatial autocorrelation characteristics of the housing conditions and types of housing conditions in China are analyzed. The correlation analysis method is used to analyze the correlation between the subtypes of housing conditions and county fundamentals (population density, urbanization, foreign population, and rental housing). The results show that: (1) the configuration of elevators is the most important indicator of the differences in housing conditions in China; (2) the better housing conditions in China are distributed on the southeast side of the “Hu Line”, while the worse areas are distributed on the northwest side of the “Hu Line”, showing significant spatial clustering characteristics, while the distribution of the different subtypes of housing conditions and their distribution in the H–H and L–L zones also have significant variability; (3) housing conditions in China’s urban areas are generally better than those in non-urban areas, and the internal infrastructure conditions of urban housing and the degree of elevator configuration are better than those in non-urban areas; and (4) the correlation between housing conditions and county fundamentals varies depending on the regional level. At the national and urban levels, a negative correlation exists between county fundamentals and housing spaciousness, although a positive correlation exists with internal infrastructure and elevator configuration. Urbanization has the greatest impact on housing conditions in these areas. In non-urban areas, there is significant variability in the correlation between county fundamentals and housing conditions.