Non-homogeneous soil’s high gravel content (also known as the “soil-rock dual structure”) may render it more prone to erosion and the significant development of gullies. In order to reveal the morphological characteristics and erosion rate of gullies in “soil-rock dual structure” areas, this study focused on the Shagou Reservoir basin in the Yimeng mountain area as the study area. Based on a complete digital orthophoto map (DOM, 0.03 m) and a digital elevation model (DEM, 0.03 m) acquired by an unmanned aerial vehicle (UAV), the researchers calculated the length (L), top width (TW), depth (D), area (A) and volume (V) of 19 gullies and built and optimized the volume estimation model. The DOM and the DEM were used to modify the morphological parameters of 43 gullies extracted from high-resolution remote sensing (RS) stereopair images (Worldview, 0.5 m), and the development and evolution of gully erosion were evaluated in large scale. The results showed that: (1) after correction, the average relative errors of parameters L, TW, D and A computed from the UAV data and the high-resolution RS stereopair image data fell below 0.005%; (2) the mean of TW/D was 5.20, i.e., the lateral erosion development of gullies far outweighed the downcutting erosion. The retrogressive erosion, lateral erosion and downcutting erosion rates of gullies were 0.01~0.83 m/a (averaged at 0.23 m/a), 0.01~0.68 m/a (averaged at 0.25 m/a) and 0.01~0.19 m/a (averaged at 0.09 m/a), respectively, between 2014 and 2021; (3) the volume-area (V-A) model for gullies is the optimal one (p < 0.01, R² = 0.944).A total of 90.7% of the gully volume was growing at an erosion rate of 0.42~399.39 m³/a and the total erosion rate of the gullies was 3181.56 m³/a from 2014 to 2021. These research findings can serve as a basis for the quantitative modeling of gully erosion in water-eroded locations with a large-dimension “soil-rock dual structure”.

Urban development of clusters situated along rivers significantly affects the health of the river ecosystems, the quality of urban environments, and the overall well-being of local communities. Ecosystem service supply value (ESSV) measures the delivery of ecosystem goods and services within a specific timeframe in a particular area. Using the lower Yellow River urban agglomeration (Shandong section) as a case, we comprehensively applied land use structure and intensity change analysis, quantitative calculation of ESS, and geographical probe methods to unveil ESS and its mechanism of response to the spatio-temporal evolution of the intensity of land use in urban agglomeration along the river. The key results were as follows: (1) Over the past two decades, farmland and construction land areas have continued to decrease and increase, respectively, with the intensity of land use change being highest from 2005 to 2010. (2) ESS has continued to rise over the past 20 years, with the income in 2020 being 11.142 billion yuan, an increase of 31.13%. The “low-value areas” are mainly concentrated in Liaocheng City, Dezhou City, and Tai’an City, which are characterized by predominantly flat terrains where farmland constitutes the principal land use type. Conversely, “high-value areas” are largely in the counties bordering the Yellow River, including the upper estuary in the north and the rugged, southeastern terrains. (3) Areas with concentrated ESSV were primarily localized in the northern estuary area and along the Yellow River in a scattered point-like pattern. The spatial distribution of hotspots has become increasingly concentrated, transitioning from points to planes. Conversely, cold spots initially increased in number before subsequently decreasing. Waterbody was the most sensitive ESSV-determining factor. (4) The spatial heterogeneity of ESSV emerges as a consequence of the interaction of multiple factors, and among these interactions, those involving NDVI and POP contain the greatest explanatory power. Our findings are expected to offer a scientific foundation for optimizing land spatial patterns and enhancing ecological management in the lower Yellow River region.

Ecosystem services value (ESV) has been one index of quantitative evaluation for the ecological livability of heavy industry cities in the new era, which is intimately relevant to patterns of spatio-temporal changes in land use. This study aims to reveal the response of ecosystem service value in heavy industrial cities to the spatial-temporal evolution structure of land use and to analyze the cold and hot spots and sensitivity. In this study, Taiyuan was taken as an example, and Landsat images were adopted as the basic data. This study used intensity analysis, revised ESV, fishing nets, sensitivity analysis, and the methods of hotspot analysis and spatial overlay. The results showed as follows, (1) The characteristics of land use structure evolution mainly focus on the increase of construction land in the early and the rapid development stage of heavy industry cities. All land use types were partly transferred to construction land, but farmland was the main source, with the largest change intensity in the rapid development stage in Taiyuan; (2) The low-value zones of ESV were mostly distributed in the main urban area for construction and farmland, while the high-value zones were primarily distributed in the forestland and grassland. They were distributed in the Fenhe River valley, western and northern mountainous and hilly areas of Taiyuan. The total ESV continued to decline from 2003 to 2018, with a loss amount of RMB 29 million; (3) The patches of land use change were more and more broken, and the spatial distribution of the cold and hot spots was more and more dispersed. The cold and hot spots of ESV were concentrated in the eastern main urban area and its surrounding areas and expanded to the north and south; (4) The forestland was the most sensitive land factor of ESV. The study provides a theoretical method for land use planning, environmental governance, and ecological restoration in heavy industry cities in the new era.

Rapid urbanization has intensified inequalities in the distribution of urban green resources, making green equity a critical concern within the framework of the United Nations Sustainable Development Goals. This study examines Zhangdian District in Zibo City, China, a representative “Whole-Area Park City” pilot area. This study integrates 1 km population density grid data with GIS network analysis, space syntax, population-weighted service pressure assessment, and a location–allocation model. Using these methods, it evaluates four categories of urban parks from the perspectives of spatial distribution, road connectivity, and social equity. The results reveal that vehicle and cycling modes achieved nearly complete 15 min coverage, whereas pedestrian accessibility remained insufficient. Walking accessibility for comprehensive parks reached 77.69%, whereas that of community parks and petty street gardens was below 33%. Population-weighted analysis further suggests that more than 78% of residents, concentrated in dense central–western neighborhoods, are served by only 21% of total park area. The Gini coefficient of per capita park area reached 0.4765, indicating substantial inequality in park green space allocation. After optimization through the addition of 76 new parks, improvements in road connectivity, and construction of a slow-traffic system, the Gini coefficient decreased to 0.4053, representing a 14.9% reduction. Meanwhile, the population below the national standard declined from 78.09% to 40.64%. These findings reflect spatial accessibility and area-based equity, while actual park service value also depends on park quality, facilities, and user behavior. This study provides quantitative evidence for equity-oriented park planning and a replicable framework for sustainable urban green space planning.

Topography critically affects the occurrence of soil erosion, and computing slope spectrum information entropy (SSIE) allows for the convenient mirroring of the patterns of macroscopic topographic variation. However, whether SSIE can be effectively utilized for the quantitative assessment of soil erosion across various types of water-erosion areas and the specific methodology for its application remain unclear. This study focused on the quantitative relationship between SSIE, the slope length and slope steepness (LS) factor within various types of water-erosion areas across different spatial scales in China using multi-source geographic information data and technical tools such as remote sensing and geographic information systems. The results revealed (1) clear consistency in the spatial patterns of SSIE and the LS factor, which both displayed a distinct three-step distribution pattern from south to north. (2) The power model (Y = A·X^B) demonstrated a superior capacity to explaining the relationship between SSIE and the LS factors compared to the linear or exponential models, as evidenced by a higher coefficient of determination (R²). R² values of different evaluation units (second-grade water-erosion area, third-grade water-erosion area, 30 km × 30 km grid, and 15 km × 15 km grid) were 0.88, 0.88, 0.81, and 0.79, respectively. (3) Despite a range of variances across various spatial scale evaluation units and different types of water-erosion areas, no significant disparities were evident within the power model. These findings offer a new topographic factor that can be incorporated into models designed for the expedited evaluation of soil erosion rates across water-erosion areas. Information about the proximity of the SSIE to the LS factor is valuable for enhancing the practical utilization of SSIE in the quantitative evaluation of soil erosion.

Extreme heatwaves threaten public health and economies. Using multi-source data from 1964–2023 and the Excess Heat Factor (EHF), we identified heatwaves and, with a generalized linear mixed model and Hurst-based intensity forecasting, assessed drivers and future trends across Belt and Road Initiative (BRI) regions. (1) Duration, frequency, and the number of events increased by 18.7 days, 21.2 days, and 5.5 events, respectively. During the 2004–2023 period, HWD, HWF, and HWN accelerated, expanding from South Asia/Middle East to Central Asia, the Caucasus, and North Asia. In 1994–2023, centroids shifted west/south: frequency 2.54° W, 1.83° S; and intensity 1.17° W, 2.79° S. (2) Between 2000 and 2019, interaction effects exceeded single effects; dominant drivers shifted from SPEI and wind speed to shortwave radiation and NDVI. (3) Future intensification peaks in East Asia, the Iranian Plateau, and China’s east coast; with H ≥ 0.7, enhanced areas exceed 33% (max 37%), concentrated in Central and western West Asia.