Magnetic susceptibility measurements are widely used to map and monitor the heavy metal pollution of soils. However, the magnetic properties of soils are influenced significantly by the bedrock lithology and soil-forming processes. Therefore, a main challenge in the data interpretation is to filter out the anthropogenic pollution signal. In this study we address this problem by analysing susceptibility values, heavy metal concentrations, as well as pedological parameters in a large soil data set from the eastern segment of Austria, covering a wide range of different lithologies and soil types. The statistic assessment demonstrates an influence of lithology and soil type on the magnetic susceptibility signal. Therefore anomalies are defined in sub sets of different soil types separately. Three different methods were applied to detect susceptibility anomalies: the median absolute deviation method, the boxplot method, and the population modelling method. These methods evaluate topsoil data only and can therefore also be applied to field measurements of magnetic susceptibility. The results were compared to the conventional method of calculating the difference of topsoil and subsoil susceptibility. All three approaches identify the main anomalies in the study area and are successful in circumventing the problem of erroneous anomaly definition due to pedological processes. However, knowledge of the lithological background is still necessary for a meaningful interpretation and can only be substituted by a large amount of data. The tested methods lead to thresholds of different height and therefore act as filters of different strength for the definition of anomalies.