In the framework of the Deep Electromagnetic Sounding for Mineral EXploration (DESMEX) project, we carried out multiple geophysical surveys from regional to local scales in a former mining area in the state of Thuringia, Germany. We prove the applicability of newly developed semi-airborne electromagnetic (EM) systems for mineral exploration by cross-validating inversion results with those of established airborne and ground-based investigation techniques. In addition, supporting petrophysical and geological information to our geophysical measurements allowed the synthesis of all datasets over multiple scales. An initial regional-scale reconnaissance survey was performed with BGR's standard helicopter-borne geophysical system deployed with frequency-domain electromagnetic (HEM), magnetic and radiometric sensors. In addition to geological considerations, the HEM results served as base-line information for the selection of an optimal location for the intermediate-scale semi-airborne EM experiments. The semi-airborne surveys utilized long grounded transmitters and two independent airborne receiver instruments: induction coil magnetometers and SQUID sensors. Due to the limited investigation depth of the HEM method, local-scale electrical resistivity tomography (ERT) and long-offset transient electromagnetic (LOTEM) measurements were carried out on a reference profile, enabling the validation of inversion results at greater depths. The comparison of all inversion results provided a consistent overall resistivity distribution. It further confirmed that both semi-airborne receiver instruments achieve the bandwidth and sensitivity required for the investigation of the resistivity structure down to 1 km depth and therewith the detection of deeply seated earth resources. A 3D geological model, lithological and geophysical borehole logs as well as petrophysical investigations were integrated to interpret of the geophysical results. Distinct highly-conductive anomalies with resistivities of less than 10 Ωm were identified as alum shales over all scales. Apart from that, the petrophysical investigations exhibited that correlating geophysical and geological information using only one single parameter, such as the electrical resistivity, is hardly possible. Therefore, we developed a first approach based on clustering methods and self-organizing maps (SOMs) that allowed us to assign geological units at the surface to a given combination of geophysical and petrophysical parameters, obtained on different scales.