The unique high/cold environment of the Qinghai–Tibet Plateau (QTP) limits the natural distribution of the population living there and threatens local residents’ health. Thus, exploring the quality of human settlements in this area is of great significance. In this study, 5 first-level indicators and 25 second-level indicators were initially selected, and the entropy TOPSIS method was used to determine the weight of each indicator and evaluate the quality of the human settlements in each county of the QTP. Then, the coefficient of variation and spatial autocorrelation were used to analyze the spatial differences in human settlement quality. Finally, the obstacle degree model was used to identify those obstacles that affect the quality of the human settlements in the QTP. This study has gathered important findings. (1) The human settlement quality in these counties can be divided into 18 high-level areas, 45 mid- and high-level areas, 44 mid-level areas, 79 mid- and low-level areas, and 28 low-level areas. (2) In terms of spatial patterns, the north is higher than the south, the east is slightly higher than the west, and the surrounding area is higher than the interior. (3) In the clustering model, the high–high clustering trend is mainly concentrated in the north of the QTP, whereas the south-central part of the QTP and the zone where Tibet, Qinghai, and Sichuan meet exhibit obvious low–low clustering. (4) The variability of human settlement quality occurs in the order of Sichuan < Yunnan < Gansu < Xinjiang Autonomous Region < Tibet Autonomous Region < Qinghai. (5) The main first-level obstacles affecting human settlement quality in the counties of the QTP are living conditions, construction level of public service facilities, and infrastructure. The main second-level obstacles are the number of living service facilities, the number of residential districts, and the density of the road networks.

A watershed ecosystem is a compound ecosystem composed of land and rivers, and its health is closely related to the sustainable development of the region it is located in. The Yihe River Basin (YRB) in central China’s Henan province, which is located in the north–south transition zone and has a mountain–hill–plain landscape from the upstream to the downstream, is adopted as the research area in this study. A watershed ecosystem health assessment system is constructed based on an ecosystem vigor–organization–resilience–service supply and demand harmony (EVORSH) framework and utilized to assess the ecosystem health in the YRB by taking a 3 km × 3 km grid as the evaluation unit. Thirteen factors are selected from natural and human social factors, and from them, the factors that influence watershed ecosystem health through the generation of spatial heterogeneity are identified using the geographical detector model. The following findings are obtained. (1) The mean value of ecosystem health levels in the YRB is 0.65 and at the good level. The ecosystem health has considerable spatial heterogeneity. The areas with high–high concentration are distributed in the mountains in the upper reaches of the YRB, and the areas with low–low concentration are mainly distributed in the plain areas in the middle reaches of the YRB. (2) The geographical detector result shows that 9 of 13 factors have a considerable impact on the spatial distribution of the YRB’s ecosystem health. The interaction between two factors is enhanced synergically. The decisive power of population density, rainfall, and potential evapotranspiration are more than 0.5, so these three are the main factors that influence the distribution of ecosystem health in the YRB. (3) The EVORSH framework is suitable for the measurement of ecosystem health in the YRB. The evaluation result is consistent with the actual situation in the YRB. A 3 km × 3 km grid is used as the basic research unit, and it can more accurately and scientifically express the spatial heterogeneity of ecosystem health in the YRB compared with the macro evaluation unit. This study can provide a scientific basis for ecological protection and high-quality development planning in the YRB. By integrating multi-dimensional data and methods, the EVORSH framework proposed in this study can quickly and scientifically assess the status of ecosystem health, identify the influencing factors of spatial heterogeneity, and could be applied in other similar watersheds.

Identifying the changes in landscape pattern and ecosystem service value (ESV) and clarifying their relationship in temporal changes and spatial variations can provide insight into regional landscape features and scientific support for regional landscape planning. Leveraging land use data from the Yihe River Basin, we quantitatively assessed the landscape pattern and ESV shifts spanning from 2000 to 2018 using the landscape pattern indexes and the equivalence factor method. We employed Pearson correlation metrics and the geographically weighted regression model to explore the interrelation of their spatiotemporal variations. Our results show the following: (1) Forestland represents the most expansive land cover category. Apart from construction land, all other types experienced a decline in area. The most notable change occurred in the area of construction land. (2) The aggregation of the overall landscape shows a downward trend. The levels of fragmentation, landscape diversity, and richness increased. (3) Throughout the entire study period, the overall ESV gradually decreased, and the land cover type with the greatest contribution to the ESV was forestland. (4) In terms of temporal changes, the patch density and edge density of the overall area are significantly negatively correlated with total ESVs. The largest values for the patch index, perimeter–area fractal dimension (PAFRAC), and aggregation are significantly positively correlated with total ESVs. (5) In terms of spatial variation, the contagion index (CONTAG), PAFRAC, and the Shannon diversity index (SHDI) were noticeably correlated with ESVs. The CONTAG is positively correlated with ESVs upstream, but negatively midstream and downstream. The SHDI is negatively correlated with ESVs upstream, but positively midstream and downstream. The PAFRAC exhibits a positive correlation with ESVs for the most part. The association between the landscape pattern indexes and ESVs exhibits temporal and spatial inconsistencies in most instances, suggesting a spatiotemporal scale effect in their relationship. This study recommends that the local government devises a long-term strategy for urban development and exercises stringent control over the unregulated expansion of construction land. Through reasonable territorial spatial planning, government departments could enhance the connectivity of the overall landscape pattern of the Yihe River Basin to achieve the reasonable allocation and sustainable development of regional resources.

A healthy rural ecosystem ensures a win–win situation for both economic growth and ecological conservation. However, the impact of land use changes at the rural level on ecosystem health remains unclear. This study focuses on the rural scale of Zheng–Bian–Luo, analyzing changes in land use from 2000 to 2020. Using the “Ecosystem Vigor-Organization-Resilience-Services” model, the study evaluates the spatiotemporal patterns of ecosystem health. The Patch-generating Land Use Simulation (PLUS) model was employed to simulate land use and ecosystem health in 2035 under three scenarios: Natural Development (ND), Ecological Protection (EP), and Cropland Protection (CP). The findings are as follows: (1) From 2000 to 2020, the area of cultivated land in Zheng–Bian–Luo rural areas decreased, and the area of forest land first decreased and then increased. (2) During the study period, ecosystem health improved as ecosystem vigor, organization, and services increased. Low-value areas of ecosystem health showed a shrinking trend, most notably in Kaifeng. (3) By 2035, under the EP scenario, forest land increased by 76.794 km², while it decreased under the CP and ND scenarios. Construction land showed an increasing trend in all three scenarios, with the ND scenario seeing the largest increase of 718.007 km². (4) In 2035, ecosystem health is projected to decline under the ND scenario due to reduced forest land and increased construction land. The CP scenario showed no significant change in ecosystem health, but the southwestern rural areas of Luoyang improved. The EP scenario saw an overall increase in ecosystem health, highlighting land use optimization as beneficial. Local governments are encouraged to create ecological protection plans balancing ecological and cultivated land protection, focusing on sensitive areas such as the Songshan region and southwestern mountainous areas of Luoyang for coordinated development.

The unique high-frigid environment and poor natural conditions of Qinghai–Tibet Plateau (QTP) have limited sustainable economic and social development. The construction of the beautiful QTP is a concrete implementation of the United Nations Sustainable Development Goals. However, identifying the progress and system coupling relationships of beautiful QTP construction entails some barriers due to data and methodological issues. To evaluate beautiful QTP construction and achieve a coordinated development regime, this paper employs an analytic hierarchy process and coupling model to quantify the comprehensive index and the coupling relationships of five subsystems (i.e., ecological environment, cultural inheritance, social harmony, industrial development, and institutional perfection) based on point of interest (POI) data, which are highly accurate, containing quantity and location information. Meanwhile, spatial autocorrelation analysis is conducted on the comprehensive index and coupling coordination degree for identifying the spatial clustering characteristics of the two. Results show that the progress of the beautiful QTP construction in most counties are under a very low or low level. For the system coupling perspective, 86% of counties are under the coupling stage indicating a strong interaction among the subsystems. However, coordination is out of harmony in most counties. For the spatial clustering characteristics, the comprehensive index and the system coupling relationships of beautiful QTP construction show a positive spatial correlation, indicating an aggregation effect. The aggregation is mostly “low–low” and “high–high” aggregation indicating the spatial differences and regional imbalances. The government should adopt measures to make the five subsystems of beautiful QTP construction more synergistic to achieve the sustainable development of the QTP. Our study formed a sample case of special areas where statistical data are scarce while constructing a technical framework of Beautiful China construction that is applicable to these areas. The findings of this study can serve as a reference for improving the beautiful QTP or other similar areas of construction.