Dynamic Remote Sensing Monitoring and Analysis of Influencing Factors for Land Degradation in Datong Coalfield

Land degradation is one of the significant ecological and environmental issues threatening regional sustainable development. Datong Coalfield is located in an arid and semi-arid ecologically fragile area and is also an important energy base, the mining of coal resources and natural factors have caused serious land degradation problems. Therefore, dynamic monitoring and influencing factor analysis of land degradation in the Datong Coalfield is particularly important for land degradation prevention and land reclamation in mining areas. This study focuses on the Datong Coalfield, using remote sensing technology to dynamically extract soil erosion, net primary productivity of vegetation, land desertification, soil moisture content. Based on the Analytic Hierarchy Process (AHP), a comprehensive assessment model for land degradation was constructed to analyze the spatiotemporal evolution of land degradation in the Datong Coalfield from 2000 to 2021, and the influencing factors of land degradation were explored using a geographic detector. The results indicate that (1) from 2000 to 2021, the land degradation level in Datong Coalfield changed to mild degradation and non degradation, with the mild degradation area increasing by 30.48% and the non degradation area increasing by 13.9%, and spatially expanding contiguously from localized areas outwards. (2) Over the past 21 years, the land degradation situation in Datong Coalfield predominantly showed an improving trend, accounting for 69.11%, indicating an overall positive trajectory. However, 0.54% of the area experienced significantly intensified land degradation, scattered in the eastern and southwestern parts of the Datong Coalfield, which are areas requiring focused governance efforts. (3) Vegetation and land use are the main factors affecting land degradation in Datong Coalfield. At the same time, the influence of land use has gradually increased over the years, and the influence of vegetation and land use interaction is the highest in the two-factor interaction.