Mineralogical and elemental data for soil discriminating and geolocation tracing

One of the key tasks of soil analysis in forensic sciences is to provide information about its diversities and geolocation. In fact, soil analysis is relevant for forensic geologists. In this study, a total of 80 soil samples were collected from eight Chinese cities (10 samples per city). Different minerals and their relative percentages were analyzed by the X-ray diffraction (XRD) method. In addition, the relative amounts of montmorillonite, kaolinite, amphibole, feldspar, calcite, and dolomite provided information about the origin of a soil, either if it came from a northern or southern city of China. The oxide weight percentages of 10 elements of Al2O3, SiO2, Fe2O3, K2O, Na2O, MgO, CaO, P2O5, MnO, and TiO2 were also obtained by using X-ray fluorescence (XRF) from the 80 soil samples. Moreover, principal component analysis (PCA) and hierarchical clustering analysis (HCA) methods were performed for dimensionality reduction, elemental marker identification and soils classification to the city they came from purposes. The eighty soils analyzed in this study could be tracked correctly to their city of origin. The K-Nearest Neighbors (KNN) model was done to evaluate the prediction ability based on the soil elemental composition, and it was confirmed by cross validation methods. The results demonstrated that mineralogical and elemental composition can provide powerful information for soil discrimination and source tracing.