Using geostatistical methods in soil magnetometry: a review

Abstract

Purpose

Soil contamination is one of the most pressing environmental problems on a global scale. However, assessing the shape and size of an area where pollution occurs, and the spatial variation in the pollution level, is a complex issue. Field magnetometry is a cheap and fast tool for soil pollution assessment. The purpose of the paper is to systematically describe the history, current state, and potential future applications of geostatistical methods in field magnetometry.

Materials and methods

The article was written based on over a hundred outstanding scientific papers describing soil research around the world using field magnetometry and geostatistical methods, combined with various secondary variables such as geochemical and diffuse reflectance spectroscopy measurements of soil as well as satellite observations.

Results and discussion

Geostatistical methods allow for the optimal use of the magnetometric method in areas with different types of soils such as forests, arable fields, meadows, fallow lands, and urban areas as well as for the determination of spatial variability parameters of magnetic susceptibility. The use of geostatistical methods in field magnetometry also allows for a more accurate determination of other soil and environmental parameters significantly affecting the value of magnetic susceptibility, which must be taken into account when conducting field measurements.

Conclusions

Both geostatistics and field magnetometry are considered groundbreaking methods in pedological research but even greater results arise from the simultaneous use of these methods. The synergy effect resulting from the use of geostatistical methods in field magnetometry allowed for the achievement of many significant scientific and practical findings. Especially, the cokriging method plays an increasingly important role in magnetometric research, thanks to the integration of magnetic susceptibility measurements with other types of measurements.

Graphical Abstract