Martial Tchantcho Amin Tazifor - DR project

Error analysis and optimization of a EMI measurement system

Doctoral Researcher: Martial Tchantcho Amin Tazifor
Local ZEA-2 Supervisor: Egon Zimmermann
Academic Supervisor: Stefan van Waasen, University of Duisburg-Essen (UDE)
Topic: Measurement Systems
Research Field: Earth and Environment

Electromagnetic Induction (EMI) Systems

Electromagnetic induction (EMI) is a non-invasive and fast geophysical measurement technique that offers the potential to obtain geological and hydrological soil properties of the uppermost meters of the subsurface with a spatial resolution in the sub-meter range. Frequency-domain EMI systems are available as portable rigid booms with fixed separations between the transmitter (Tx) and the receiver (Rx) and they measure the apparent electrical conductivity (σa) of the sensed soil volume by inducing electrical currents and measuring the resulting electromagnetic fields. The sensing depth of EMI instruments depends on the sensor configuration and in particular the coil orientation and Tx–Rx separation.

Error analysis and optimization

Martial Tchantcho Amin Tazifor's DR project
Schematic of a EMI system

The measurement of electrical conductivity using electromagnetic induction (EMI) is a method for rapid 3D mapping of agricultural land that supports environmental and climate relevant modelling of transport processes in the soil. Howevermost EMI systems currently do not provide absolute σa values, rather erroneous shifts in measured data occur due to calibration problems and ambient temperature drifts, which hinder a reliable inversion of the data. This creates the need for the development of new model-based measurement methods that both improve depth resolution and minimize the negative effects of temperature drifts on electromagnetic induction systems. Such a model-based method for the correction of temperature-dependent measurement errors should predict the dynamic temperature behaviour of the measurement system with regard to phase drift and with this approach significantly increase the measurement accuracy.


Last Modified: 12.07.2023