The scientific analysis of spatial-temporal differentiation characteristics and driving factors of illegal land use is of great significance for the formulation and optimization of policies to control the emergence of illegal land use. This paper establishes two variable systems of illegal land use and its driving factors, defined the multidimensional characteristic variables of illegal land use and analyzes the relationships among them by the Pearson’s correlation coefficient; In addition, the spatial–temporal characteristics of each variable of illegal land use from 2004 to 2017 are described by the spatial autocorrelation analysis; Finally, based on the geographical detectors, the influence direction and degree of the factors of economic structure, social structure and land market behavior on the characteristics of different illegal land use are studied. The results show that the spatial agglomeration of different characteristics of illegal land use had been weakening from 2004 to 2017, but the rate of weakening was different, and L-L agglomeration changed between Xinjiang and other central-western provinces, H-H agglomeration changed in the coastal regions of the central-eastern of China, the level and ability of the central government and local governments to govern illegal land use is constantly improving on the whole; the compositional factors of economic development structure, social development structure, and land market behavior of driving factors had different influence in the degree, the location or the direction of different characteristics of illegal land use. According to the spatial–temporal characteristics and the differences of driving factors, managers can formulate differentiated illegal land use control policies, which will help to control the occurrence of illegal land use and help the settlement of illegal land use cases, and ultimately achieve sustainable development.

Land consolidation is essential in China for improving land use efficiency and supporting rural public space governance. Previously, the implementation of land consolidation projects (LCPs) had been mainly led by governments in China. In recent years, the Chinese government vigorously promoted land consolidation, and land consolidation in the corporation-leading mode (CLM) has emerged. This study focused on investigating the performance of CLM projects and the difference in performance levels between the CLM projects and the government-leading mode (GLM) projects. Based on the improved extensible matter–element model, the performance levels of 14 LCPs in GLM and CLM of Jianghan Plain, Hubei Province and related impact factors were analyzed. A set of evaluation indices was selected based on the “process-based thinking and logic”. Results showed that: (1) performance levels of the 14 LCPs are different, most of the projects in the GLM have ordinary or poor performance, while most of the projects in the CLM have excellent or good performance; (2) factors affecting the performance levels of LCPs are also different in the two modes. The main influencing factors in the CLM were the poor access to field roads, insufficient shelterbelt planting, and low land reclamation efficiency, while the insufficient shelterbelt planting, low annual output value of farmland and grain production capacity, low increase rate of agricultural labor production, and low land reclamation efficiency were the main influencing factors in the GLM; (3) comparative analysis of the two modes revealed that LCPs in the CLM have clear investment directions, high output benefits, and obvious advantages in the development of modern agriculture when compared with the GLM. To achieve improving the performance levels of LCPs, policy makers should actively innovate the implementation mode of LCPs and encourage all kinds of agricultural corporations to participate in land consolidation.

The Middle Route Project of China’s South-to-North Water Diversion Project (SNWDP) is a national-level water source protection zone and the ecological safety of its water quality and surrounding soil is of great significance. In this study, heavy metals in the surface water and topsoil in the core water source area were quantitatively analyzed using a geographic information system (GIS) and geostatistical techniques combined with environmental pollution and ecological risk assessment models to determine their environmental contamination levels, ecological risk levels, and spatial distribution patterns. Cd was identified as an essential factor responsible for the overall slight heavy metal pollution in the topsoil layer. Heavy metal contamination in surface water was primarily driven by alert-level concentrations of Hg and was consistently distributed in areas with high concentrations of Hg in the topsoil. Applying the potential ecological risk index (RI) revealed two key results. First, surface water showed no ecological risk. The concentrations of heavy metals in surface water met the goals set by relevant authorities in China. Second, overall, the topsoil was at low ecological risk, with a spatial pattern primarily influenced by Cd and Hg. Some heavy metals might have similar pollution sources and originate from human activities such as industrial activities, mining and smelting, and pesticide and chemical fertilizer applications. The study is important for improving the soil and water ecology in the reservoir area and ensuring the northward diversion of high-quality water. In addition, it provides a sound basis for making decisions about local heavy-metal remediation and treatment projects.