Geoscientific Instrumentation,
Methods and Data Systems 

UAV-borne magnetometry has gradually become an important tool for geophysical studies. However, developing such a UAV-borne aeromagnetometry system is challenging owing to strong magnetic interference introduced by onboard electric and electronic components. One static and two dynamic experiments were conducted to understand the platform's magnetic interference. The results reveal that the strongest magnetic interference is from some current-carrying cables.

The baseline wander has special characteristics, such as being low frequency, large amplitude, non-periodic, and non-stationary. It is caused by the receiving coil motion and always exists in the process of data acquisition. The proposed method can be used to solve similar problems. This paper has the following highlights: (1) the method can be used to process non-periodic and non-stationary signals; (2) the method is adaptive to satisfy the stopping criterion based on the measured signal.

In times of global warming, permafrost is starting to degrade at alarming rates, requiring new and improved characterization approaches. We describe the design and test installation, as well as detailed data quality assessment, of a monitoring system used to capture natural electrical potentials in the subsurface. These self-potential signals are of great interest for the noninvasive investigation of water flow in the non-frozen or partially frozen subsurface.

Our knowledge of the Earth's magnetic field arises from magnetic signals stored in lavas. In rugged volcanic terrain, however, the magnetization of the underlying flows may influence the magnetic field as recorded by newly formed flows on top. To measure these local magnetic anomalies, we developed a low-cost field magnetometer with superior accuracy and user-friendliness. The first measurements on Mt. Etna show local magnetic variations that are much larger than expected.

In this paper, we present an approach to represent underlying errors in measurements and physical models in the temporal gravity field determination using GRACE observations. This study provides an opportunity to improve the error model and the accuracy of the GRACE parameter estimation, as well as its successor GRACE Follow-On.