Weighted Information Models for the Quantitative Prediction and Evaluation of the Geothermal Anomaly Area in the Plateau: A Case Study of the Sichuan–Tibet Railway

The prediction of geothermal high-temperature anomalies along the plateau railway will be helpful in construction project and its later management. Taking Sichuan–Tibet as study area based on Landsat8 thermal infrared images, map data, measured data regarding cause distribution anomalies, through correlation analysis, we selected six impact factors including LST, combined entropy geological formation, fault density, buffer distance to rivers, magnetic anomaly, earthquake peak acceleration input maps model. index-overlay information model, weights evidence model were established quantitatively predict anomaly area, divided into four classes. results show that achieved a high accuracy; success index ratio reached 0.0053% 0.872, respectively, spatial points is basically consistent with results. This research can act reference for design railway.