GeoHealth Environmental Suitability Assessment of Oroqen Autonomous Banner in Inner Mongolia

Human health is closely related to the geological environment, with elements such as geological background, water, soil, air, and living organisms significantly influencing population health. A single-perspective assessment of geological environment suitability is limited in its ability to capture the interactions among multiple factors. To investigate the extent to which regional geological environments affect human health, this study takes the Oroqen Autonomous Banner in Inner Mongolia as a case study. Addressing the challenges of integrating multi-indicator data and weighting methods, a multi-indicator interaction-based suitability evaluation system for the geoHealth environment was developed, encompassing three major categories—geological conditions, geographical conditions, and ecological conditions—and 11 subcategories. A geoHealth environmental suitability assessment was conducted, and the weight indices for each indicator were determined using a combined weighting method that integrates the Analytic Hierarchy Process (AHP) and an improved CRITIC method. One-at-a-Time (OAT) sensitivity analysis was performed to verify the stability of the evaluation results. Finally, spatial autocorrelation analysis was employed to elucidate the spatial distribution patterns of the geoHealth environment in the Oroqen Autonomous Banner. The evaluation results indicate that the geoHealth environmental suitability of the Oroqen Autonomous Banner can be classified into five grades. The first-grade suitable area for geoHealth covers 1,876 km², accounting for 17.26% of the study area. These areas are primarily distributed in the northeastern region and around mountain valleys, significantly influenced by factors such as topography, soil, and mineral elements. Spatial autocorrelation analysis reveals a clustering of similar values in the geoHealth environment of the Oroqen Autonomous Banner, with extremely high suitability observed in the eastern parts of Dayangshu Town and Guli Township. In the sensitivity analysis, the maximum absolute average change rate (MACR) was 2.2354%, significantly lower than the weight change rate of 30%, indicating that the evaluation results are relatively stable overall and the weight settings are reasonable. This evaluation method effectively reflects the geoHealth environmental suitability of the Oroqen Autonomous Banner, and the results are scientifically reliable.