A multi-parameter approach for recognition of anthropogenic noise in aeromagnetic data collected over populated areas: Erzgebirge, Germany

Aeromagnetic data is routinely acquired by mineral exploration programs. The objective is to obtain a raster image of the spatial variations of magnetic field intensity, these variations are associated with mineralogical variations in the subsurface. When the survey is conducted in a populated area much of the signal, however may be associated with anthropogenic sources such as buildings and roads. Identification, and minimisation of the anthropogenic related signal then is essential to derive a useful product for geological mapping. In this work we examine a scalar magnetic dataset from Geyer, Saxony, and we apply five approaches for locating regions of anomalous anthropogenic signal: signal amplitude, absolute 4th difference, signal standard deviation, enhanced horizontal gradient, and curvedness. All are shown to produce similar responses, and the summation of the five results compares favorably with the standard Keating kimberlite (circular anomaly) approach for detecting anthropogenic signals. Complications arise when geological features produce signals of similar amplitude to anthropogenic sources. Differentiating the probable origin of any specific pattern can be assessed by using a 2D shape index and increased flight height. Verification of an anthropogenic anomaly is achieved by comparison of anomalous solution grids with GIS based reference data.