Extraction of the stable component of electrical surveys of soils and the consequence on the mapping of their thicknesses

•AFACK enables to capture non-stationary effects affecting a spatio-temporal signal.•A significant improvement of a spatio-temporal signal is achieved thanks to AFACK.•AFACK provides the ability to get rid of conjectural factors affecting a signal.•Mono-temporal electric surveys lead to various patterns of a static soil property.•Stable components of electrical surveys are relevant to map a static soil property. Knowledge of the spatial variability of soil thickness (ST) in agricultural fields is useful for improving crop management. Spatial patterns of ST can be characterized using temporal stability analysis of high spatial density and temporal frequency data, associated with sparse and difficult to obtain data on the target variable. Apparent electrical resistivity measurements of soil at high spatial density have been widely used to infer the spatial variability of soil properties. However, electrical resistivity measurements are sensitive to many factors (e.g. soil water content). Thus, it remains difficult to interpret them according to a characteristic of the soil such as its thickness. The objective of this study was to present a geostatistical approach called automatic factorial cokriging (AFACK), which allows capturing the time-invariant part between the spatio-temporal measurements of a signal, called stable component in the sequel. The stable component achieved by AFACK was then used as a covariate in a multivariate estimation algorithm to map a static soil property pattern. The underlying idea was to highlight that the spatial estimates of a static soil property pattern is well achieved by integrating, in a multivariate estimation algorithm, the stable component over the time of a covariate instead of its single acquisitions. The latter generally show weak and inconsistent relationships with the static properties of the soil such as its thickness. These inconsistent relationships are mainly generated by the temporal variability of the signal measurements carried out under various conditions. Through three surveys of soil resistivity measurements carried out on three dates on the soil of an agricultural plot, results revealed that AFACK allows: (i) reproducing an initial signal deliberately corrupted by a noise, (ii) extracting the time-stable component of two or more soil electrical resistivity surveys. Cluster analysis results also revealed that the time-stable component of the signal exhibits well homogeneous areas in space conversely to sur