Terrain feature points, such as the peaks and saddles, are the basic framework of surface topography and its undulations, which significantly affect the spatial distribution of surface topography. In the past, terrain feature points were extracted separately for each type, while the internal connections between the terrain feature points were ignored. Therefore, this work proposes an integrated algorithm for extracting terrain feature-point clusters, including the peaks, saddles and runoff nodes, based on the DEM data. This method includes two main processes: positive terrain-constrained ridgeline extraction and terrain feature-point cluster extraction. Firstly, a threshold determination method of flow accumulation in the hydrological analysis is proposed by combining morphological characteristics with runoff simulation, and the ridgelines are extracted based on this threshold. Subsequently, the peaks and their control areas are extracted by space segmentation. Meanwhile, the saddles and runoff nodes are obtained by spatial intersection. Finally, the integrated terrain feature-point clusters are obtained by merging the three extracted terrain feature points. This method was experimented with in the six typical sample areas in Shaanxi Province and verified its results by contour lines and optical images. It shows that the spatial positions of the extracted terrain feature clusters are accurate, and the coupling relationships are great. Finally, the experiments show that the statistical attributes of point clusters and their spatial distribution trends have an obvious correlation with geomorphic types and geomorphic zoning, which can provide an important reference for geomorphic zoning and mapping.

Assessing the impact of land use and land cover change (LUCC) on soil erosion by wind and water is crucial for improving regional ecosystem services and sustainable development. In this study, the Revised Wind Erosion Equation (RWEQ) and Revised Universal Soil Loss Equation (RUSLE) were used to reveal changes in the extent of soil erosion by wind and water in the Qaidam Basin from 2000 to 2018 and the impact of LUCC on them. From 2000 to 2018, with global climate change, the areas and intensities of soil erosion by wind decreased, whereas those of soil erosion by water increased. With increased human activities, approximately 12.96% of the total area underwent conversion of the type of use: the areas of cropland, woodland, grassland, and construction land increased, whereas the areas of shrubbery, desert, and other unused land decreased. Land use/cover changes are positive to the soil erosion of water but negative to the soil erosion of wind. Among them, the changes in vegetation coverage of other unused land and grassland contributed to 83.19% of the total reduction in soil erosion by water. Converting other unused land to grassland reduced the total reductions in soil erosion by wind by 94.69%. These results indicate that the increase in vegetative cover and area of grasslands in the Qaidam Basin had a positive impact on the reduction in soil erosion. It is recommended that the arrangement of grasses, shrubs, and trees be optimized to prevent compound erosion by wind and water for protecting regional ecological environments.

Check dams play an irreplaceable role in soil and water conservation in the Chinese Loess Plateau region. However, there are few analyses on the connection between check dams and the downstream channel and the impact on structural connectivity and sediment interception efficiency. Based on a field survey, this study classified the connection mode between check dams and the downstream channel, and the actual control area percentage by discharge canal in dam land was used to quantitatively evaluate the degree of the structural connectivity of sediment between the check dam and the downstream channel. The analysis results show that the connection mode can be divided into eleven categories with different structural connectivity. The different connection modes and its combination mode of check dams and downstream channels in dam systems have a large difference, and the structural connectivity of the dam system is less than or equal to that of the sum of single check dams in a watershed. The degree of structural connectivity of a dam system will be greatly reduced if there is a main control check dam with no discharge canal in the lower reaches of the watershed. Compared with a single check dam, the structural connectivity of a dam system is reduced by 0–42.38%, with an average of 11.18%. According to the difference in connection mode and structural connectivity of check dams and dam systems in the four typical small watersheds, the optimization methods for connection mode in series, parallel and hybrid dam systems were proposed. The research results can provide a reference for the impact of a check dam on the sediment connectivity and the sediment interception efficiency in a watershed and can also guide the layout of a dam system and the arrangement of drainage facilities.

Resource-based cities, characterized by a prolonged dependence on resource extraction and persistent urban expansion, frequently exhibit significant imbalances between the supply and demand of ecosystem services (ESs). Understanding how various types of resource-based cities respond to urbanization in terms of ESs supply–demand relationships is crucial for advancing sustainable urban development. This study examines three representative resource-based cities in Sichuan Province—Nanchong (growing), Luzhou (declining), and Panzhihua (mature)—to analyze changes in six key ESs from 2000 to 2020, including soil retention, carbon sequestration, water yield, habitat quality, food production, and recreational services. Ordinary least squares (OLS) regression and random forest (RF) models were employed to evaluate the effects of gross domestic product (GDP) density, construction land proportion (CLP), and population (POP) density on the ecosystem service supply–demand ratio (ESDR), and to explore variations in sensitivity among these cities. The results demonstrate that (1) ESs’ supply–demand patterns differ significantly among the three city types. Nanchong exhibited a declining supply and increasing demand for regulating services; Luzhou displayed improvements in its water yield and recreational services but persistent degradation of habitat quality; and Panzhihua achieved notable gains in carbon sequestration and habitat quality. (2) Urbanization generally reduced the ESDR across all three cities. However, the GDP density positively influenced the ESDR in Nanchong, while the CLP and the POP density exerted widespread negative effects. In Luzhou, the ESDR was primarily constrained by the CLP, whereas in Panzhihua, both the CLP and the POP density significantly reduced the ratio. (3) The sensitivity analysis revealed distinct response patterns: Nanchong was most sensitive to CLP, Luzhou responded most strongly to GDP density, and Panzhihua was highly sensitive to both GDP density and POP density. These findings underscore the necessity of formulating city-type-specific development strategies—such as land restoration, population control, and industrial upgrading—tailored to different types of resource-based cities, in order to reconcile urbanization with ecosystem service dynamics, promote green transformation, and contribute to the achievement of the Sustainable Development Goals (SDGs).

Data interpolation methods are important statistical analysis tools that can fill in data gaps and missing areas by predicting and estimating unknown data points, thereby improving the accuracy and credibility of data analysis and research. Different interpolation methods are widely used in related fields, but the error between different interpolation methods and their interpolation fusion optimization have a significant impact on the interpolation accuracy, which still deserves further exploration. This study is based on two different types of point data: PM_2.5 (PM_2.5 refers to particulate matter in the atmosphere with a diameter of 2.5 μm or less, also known as inhalable particles or fine particulate matter) in Xinyang City, Henan Province, and the elevation of typical gullies in Yuanmou County, Yunnan Province. Using relative difference coefficients and hotspot analysis methods, the differences in error characteristics among four interpolation methods, ordinary kriging (OK), universal kriging (UK), inverse distance weighted (IDW), and radial basis functions (RBFs), were compared, and the influence of interpolation fusion methods on the accuracy of interpolation results was explored. The results show that after interpolation of PM_2.5 concentration and gully elevation, the error difference between OK and UK is the smallest in both datasets. For PM_2.5 concentration data, IDW and UK interpolation errors have the largest difference; for elevation data, the differences between RBF and UK interpolation are the largest. The weighted fusion results show that the interpolation error accuracy of PM_2.5 concentration data with an interpolation point density of 0.009 points per square kilometer is improved, and the root mean square error (RMSE) after fusion is reduced from 0.374 μg/m³ to 0.004 μg/m³. However, the error accuracy of the elevation data of the gully with an interpolation point density of 0.76 points/m² did not improve significantly. This indicates that characteristics such as the density of the original data are important factors that affect the accuracy of interpolation. In the case of sparse interpolation points, it is possible to consider fusing the interpolation results with different error patterns to improve their accuracy. This study provides a new idea for improving the accuracy of interpolation errors.

With the deepening of urbanization in China, the coordinated development of cities in different regions is an important part of the sustainable development of the country, and the reasonable quantification of the unbalanced development of cities in different regions is an important issue facing the society nowadays. Previous studies usually use population data to analyze the power-law distribution law to quantify the imbalance of urban development in different regions, but China’s population data span a large number of years and numerous division criteria, and the results obtained from different population data are widely disparate and have obvious limitations. The paper starts from a fractal perspective and utilizes OpenStreetMap (OSM) data to extract national road intersections from 2015 to 2022, calculates critical distance thresholds for eight years using urban expansion curves, generates urban agglomerations in China, and quantifies the imbalance of urban development in different regions by calculating the urban agglomeration power-law index. The results indicate that (1) the critical distance threshold of urban expansion curves exhibits a slight overall increase and stabilizes within the range of 120–130 m, (2) the number of urban agglomerations in China has been increasing significantly year by year, but the power-law index has been decreasing from 1.49 in 2015 to 1.36 in 2022, and (3) the number of urban agglomerations and the power–law index of the Beijing–Tianjin–Hebei, Yangtze River Delta, Pearl River Delta, and Chengdu–Chongqing regions, which is consistent with the national scale trend, indicates that the scale distribution of urban agglomerations in China at this stage does not conform to Zipf’s law, and there is a certain Matthew effect among cities in different geographic areas with a large unevenness. The results of the study can provide new ideas for assessing the coordinated development of cities in different regions. It compensates for the instability of population and economic data in traditional studies.