The Chinese Loess Plateau (CLP) is known for its complex topography of hills and gullies, and lots of human land-use management activities have been put into practice to sustain the soil, water and other natural resources. Afforestation has been widely applied on the CLP and it’s important to understand the effects of topography on these planted trees. However, the coarse spatial resolution of remote sensing data makes it insensitive to local topography, and the traditional in-situ measurements would consume vast amounts of time and resources. In this study, a small headwater catchment of the CLP was selected to study the effects of topography on the planted trees. Low altitude unmanned aerial vehicle based light detection and ranging (UAV-based LiDAR) technology was utilized to obtain high-resolution topography and vegetation structure data. Results showed that the middle transition zone (mid-transition, slope > 45°) was an important boundary of topography in the gully area of the CLP. In the forested catchment, the area of the mid-transition zone had the lowest of tree density, canopy coverage and leaf area index due to steep slope gradient. The tall trees ten to twenty meters high were concentrated in the downhill area, which had the highest canopy coverage and leaf area index. Elevation had significant linear relationships with canopy coverage and leaf area index (p < 0.001), which revealed the impact of topography on the forest indexes of the afforestation catchment. We concluded that the high-resolution LiDAR technology facilitated the research of topography and forest interactions in land surface.

Coal mining inevitably brings some negative impacts, such as surface subsidence, aquifer breakage, and land degradation, to the eco-geological environment in the mining area. Among these impacts, coal mining-induced ground deformation is the most serious and has threatened the geological, ecological, and human settlement securities of mining areas. Efforts existing in the literature apply to ground deformation identification in mined-out areas at the meso-/micro and short-time scales. However, when looking back at coal mining history, there are few ways to quickly and accurately quantify ground deformation at the regional and long-time scales. In this context, we propose a method for identifying ground deformation patterns in coal mining areas using historical high-precision digital elevation models (DEMs), including data preprocessing, DEM subtraction operations, interpretation, and fitting correction. This method was applied to the Yulin National Energy and Chemical Base and successfully identified the ground deformation characteristics of the Yulin coal mining area from 2015 to 2019. By determining surface subsidence displacement, excavation depth, stacking height, and the position of the goaf suspended roof area, the objective situation of ground deformation in Yulin mining area was obtained, and the mining methods and distribution characteristics of different surface deformations were analyzed and determined. The research results are of great significance for the development of mineral resources in mining areas, reducing geological disaster risks, protecting the ecological environment, and achieving the goal of coordinated development in mining areas.

Groundwater resources are essential for sustaining ecosystems and human activities, especially under the pressures of climate change. This study employed Electrical Resistivity Tomography (ERT) to assess the impact of Gully Land Consolidation (GLC) engineering on the groundwater hydrological field of small watersheds in the China Loess Plateau (CLP). Results revealed ample subsurface water storage in backfilled areas, primarily migrating along the original river path owing to topographical limitations. Although the distribution patterns of soil moisture in each backfilling block varied slightly, the boundaries of soil moisture content and variation mainly appeared at depths of 8 m and 20 m underground. Significant moisture variation occurred across the 0–20 m underground layers, suggesting the 8–20 m layer could function as a groundwater collection zone in the study area. Human activities could disturb groundwater, altering migration pathways from the original river path. An optimized “Drainage–Conveyance–Barrier” system is proposed to enhance GLC sustainability, involving upstream groundwater level control, midstream soil moisture management, and downstream hydrological connectivity improvement. These findings carry substantial implications for guiding the planning and execution of GLC engineering initiatives. The novelty of this study lies in its application of ERT to provide a detailed spatial and temporal understanding of soil moisture dynamics in the GLC areas. Future research should focus on factors such as soil types and topographical changes for a comprehensive assessment of GLC’s impact on small watershed groundwater hydrology.

Coal mining provides energy and economic benefits but also causes environmental damage, including land degradation, pollution, and surface temperature anomalies. Underground coal fires can severely impact the environment, leading to abnormal heat, ground deformation, and ecological harm. Using Landsat-9 imagery and meteorological data, we developed a new threshold-based method to detect large-scale land surface temperature anomalies (LSTAs). By analyzing multiple images from November to February, we improved the accuracy of this method. The LSTA data were integrated with topographic indexes and different coal seam depths to filter irrelevant points. A Wilcoxon test, correlation analysis, and linear regression were performed with the LSTA multi-data matrix to quantify the relationships between the topographical and temperature indexes. The results revealed significant differences in elevation (relative elevation), slope, and TWI across different coal seam depths (p < 0.001). LST distribution in November, December, and February was significantly different among the three different seam depth units (p < 0.001). Relative elevation strongly correlated with temperature. The relationship between relative elevation and temperature may change seasonally due to seasonal climatic fluctuations and heterogeneous underlying surface characteristics.