The management-based methods to control heavy metals pollution need the quantitative information about heavy metals levels. Moreover, determination of hotspots could help to make a suitable decision. The anomaly delineation maps of heavy metal provide an integrated view of their position, amount and distribution. These could be used by decision makers for data analysis, defining the probable pollution source and planning a pollution control program. The main purpose of this study was to determine spatial distribution of As, Sb, Cr, Cd, Ni, Co, Cu, Zn, Pb, Fe and V in the surface soils of Hamadan province, create a holistic view to position, level and anomaly of (PCA), False Color Composition (FCC), Inverse Overlay Method and Weighted Linear Composition (WLC). In this order, 286 surface soil samples (0-20cm) were collected using systematic random sampling and the total concentrations of heavy metals were measured. The distribution maps of heavy metal concentrations were generated by radial basis function, ordinary and disjunctive Kriging. The Kriging methods precision of different models was compared by Mean Absolute Error (MAE) and Mean Bias Error (MBE), and the method with higher precision was selected to mapping the heavy metals concentrations in the soil. Overlaying the heavy metals distribution maps with geology and land use maps showed that As, Fe, Cd, Zn, Cr, Co, Ni and Sb have geological origin, Cu and V have originated from agriculture and geology. Lead concentration is controlled by geological formation, agricultural activities and also urban pollution. The elements were combined in four color composition method. The first element layer obtained from FCC method was overlaid with the third layer and second layer with fourth layer in an inverse manner. Finally, weighted linear composition was done on fuzzy data of two element Zn, V, Pb, Fe is disjunctive Kriging by exponential model and for Ni, Co, Cr, Sb is ordinary Kriging by exponential model. Cd, and Cu were interpolated by radial basic method. Based on principal component analysis, the heavy metals situated in 4 factors. The first component included Zn, V, Ni, Cr, Co, As, and Fe. The second component contained Cu and Cd. Pb was located in the third component, As and Sb in the fourth component. Generally, the high positive association in any Keywords Kriging, Heavy metals, Principal Components Analysis, False Color Composition, Inverse Overlay Method, Weighted Linear Composition
