- 1Forschungszentrum Jülich GmbH, Institute of Technology and Engineering (ITE), Jülich, Germany
- 2Institute of Bio- and Geosciences (IBG-3) - Agrosphere, Forschungszentrum Jülich GmbH, Germany
- 3Faculty of Mechanical Engineering (ISF), RWTH Aachen University, Germany
Precision agriculture is increasingly using rapid and non-invasive methods to characterise soil properties and monitor field status, with the aim of enabling efficient and sustainable management. Electromagnetic induction (EMI) can be used to rapidly measure the electrical conductivity of the soil and thereby provide information about the soil complexity, water content dynamics, and nutrient availability. The use of Unmanned Aerial Vehicles (UAVs) allows measurements of soil properties on cultivated land and makes the method independent from field conditions.
We developed a lightweight, scalable EMI sensing platform with a fast data acquisition for deployment on hexacopters in the 25 kg class. The system has one transmitter and four receivers with variable coil pair distances of 1.5 m, 1.9 m, 2.3 m, and 2.7 m. The EMI system weighs less than 5 kg and allows a measurement time of approximately 15 minutes with a fully charged 100 Wh battery from a DJI600 UAV. The apparent conductivity values are recorded at a measurement rate of 10 Hz. WLAN communication, MQTT-based protocols, a TimeScale database and a web-based measurement interface enable real-time display of the data.
During the initial test and evaluation phase, EMI measurements are carried out using a UAV at several defined measurement points and at multiple elevation levels across the test field near Jülich, Germany. The goal of the test was to (a) identify the UAVs electromagnetic interference on EMI measurements at different distances from the drone, to (b) assess the feasibility of vertical measurements at different altitudes, to (c) determine reference conductivity values using a commercial EMI system at several positions on the ground, to (d) record corresponding housekeeping data from DGPS and onboard position sensors and to (e) perform a potential offset calibration based on the acquired datasets.
How to cite: Dick, M., Mester, A., Zimmermann, E., Wüestner, P., Ramm, M., Scherer, B., Bernard, J., Dogar, S. S., Montzka, C., Brogi, C., Huisman, J. A., and Natour, G.: Drone Based Field Measurements of a Lightweight Electromagnetic Induction System (SELMA-TF) for Agricultural Applications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12457, https://doi.org/10.5194/egusphere-egu26-12457, 2026.