Objective  Models for classifying and predicting human health risk of in-situ leaching sites of ionic rare earth ore were established for ecological restoration and pollution control of the leaching sites.

  Method  Taking Longnan County, Jiangxi Province as the study area, spatial distribution of in-situ leaching sites of ionic rare earth ore was obtained by using human-computer interactive interpretation. A fuzzy analytic hierarchy process method was established for classifying the leaching sites. Random forest, lifting regression tree, C5.0 decision tree and weighted integration models were used for predicting human health risk probability of the leaching sites. The inverse distance weighted interpolation method was used to map the spatial distribution of human health risk probability around the leaching sites.

  Results  The leaching sites in Longnan County were mainly located in the mountainous and hilly areas with a slope of less than 25° in the northeast of the county. The area of the leaching sites was the most important variable to classify the leaching sites by using the fuzzy analytic hierarchy process. In the concentrated distribution area of the leaching sites, the risk gradually increased from the second type (with a low risk) to the fourth type (with a high risk) from northeast to southwest of the leaching sites. Random forest model (R² = 0.744) outperformed the lifting regression tree and the C5.0 decision tree models for predicting the human health risk of the leaching sites. A simple weighted integration method can further improve the prediction of human health risk. The risk was high in the middle and low in the east and west of the concentrated distribution area of the leaching sites. The risk was high within about 3 500 m around the leaching sites and low beyond the distance.

  Conclusion  The fuzzy analytic hierarchy process can be used to reasonably classify the leaching sites of ionic rare earth ore. The random forest model was the optimal model for predicting the human health risk of the leaching sites.