(1) Background: The Henan section of the Yellow River Basin plays an important role in the economic zone of the middle reaches of the Yellow River. However, ecological environmental geological problems such as soil erosion have seriously affected the lives of residents and economic development, resulting in increasingly prominent conflicts between humans and the environment. Therefore, this paper made use of remote sensing images and other reference data, integrated image classification, remote sensing inversion and statistical analysis methods to explore the ecological environmental geological problems and their causes in the Henan section of the Yellow River Basin. (2) Results: the main eco-environmental geological problems in the Sanmenxia–Zhengzhou section are serious soil erosion, degradation of water conservation function and being prone to geological disasters. The main eco-environmental geological problems in the Zhengzhou–Puyang section are poor water and soil conservation function, degradation of water conservation function and poor biodiversity maintenance function. In the last 19 years, the eco-environmental geological problems in the Henan section of the Yellow River Basin have shown a significant improvement trend as a whole. Along the main stream of the Yellow River in Sanmenxia, Luoyang, Jiyuan, Jiaozuo, Zhengzhou and other areas, the eco-environmental geological problems are still prominent; altitude, vegetation and rainfall are the key driving factors of eco-environmental geological problems in the Sanmenxia–Zhengzhou section and rainfall, vegetation and land-use type are the key driving factors in the Zhengzhou–Puyang section. (3) Conclusions: This study comprehensively considered the three aspects of ecology, environment and geology in a total of five research topics. The temporal and spatial distribution characteristics and driving factors of ecological environmental geological problems in the Yellow River Basin were analyzed, which could provide technical support for ecological environmental protection and high-quality development in the Yellow River Basin.

To address the separated organization of structural and attribute information in three-dimensional geological modeling for coal mine production, this study presents a three-dimensional geological structure–property coupled modeling method implemented through an integrated voxel-based workflow. A regular voxel model is used as a unified spatial carrier to organize stratigraphic structures, coal seams, boundaries, reserve parameters, and gas content attributes within the same spatial framework. Structural information is first identified under surface and boundary constraints, and attribute values are then assigned within structurally constrained voxel domains. Using production data from the Hemei No. 3 Mine, the method was applied at both mine and working-face scales to evaluate its implementation, engineering consistency, sensitivity, and uncertainty. The results show that the proposed method can jointly represent the coal seam geometry and gas content distribution and can support spatial query and reserve updating. At the mine scale, the voxel-based reserve estimate for the No. 2-1 coal seam differed from the traditional geological block estimate by 1.67%. At the working-face scale, as an engineering consistency check, the relative difference between the voxel-based estimate and the engineering reference estimate decreased from 31% to 8.4% after additional borehole constraints were incorporated. Additional validation and sensitivity tests yielded quantified errors for gas content and working-face coal-seam geometry estimation. The results further show that reserve estimates are affected by voxel resolution and apparent density assumptions, whereas the spatial distribution of gas content estimates is affected by the tested IDW parameters. Therefore, the proposed method provides a practical application-oriented modeling and updating method under the data conditions of the case study, while broader transferability requires further independent validation and more systematic uncertainty analysis.