## 3 Landslide Monitoring  
Landslide investigation is one of the more consolidated applications of the ERT method. The main contributions of the static 2D and 3D ERT (Figure 2) tomographic methods regard the delineation of the geometry of the landslide bodies and the identification of high water content areas [42; 44; 71]. As it concerns the _landslide monitoring_, the TL-ERT method represents an optimal tool to investigate the triggering factors of mass-movements related to water infiltration, and soil moisture's temporal and spatial changes. In fact, the time series of the resistivity images are strongly influenced by the time-dependent changes of water content in soil and subsoil. [PERSON] et al., 2010 [72] performed a field experiment at the Vence landslide (France), considered as a translational landslide, including 1.2 \(\times\) 10\({}^{6}\) m\({}^{3}\) of material. They measured rainfall precipitation for three months, including water level and resistivity values, and investigated the possible correlations between these parameters. The study was carried out using raw data (apparent resistivity values) without any inversion, the results pointed out the strong negative correlations between the rainfall events and the resistivity correlation factor, and between the piezometric elevation and the resistivity average. [PERSON] et al., 2012 [73] carried out another field experiment at the Laval landslide (France). Starting from a non-saturated condition near the surface, the TL-ERT measurements were performed during water infiltration within clay-shale material. They observed a reduction of resistivity values (18%) with an asymptotic value in correspondence to steady state flow conditions. The inversion of the TL-ERT data was carried using different methods [2; 49], and the results highlighted possible preferential flows near the landslide toe in the steady stationary flow (Figure 3). Other field experiments planned for landslide investigations in Taiwan and Italy are reported in [PERSON] et al., 2012, [PERSON] et al., 2012, and [PERSON] et al., 2017 [74; 75; 76]. \begin{table}
\begin{tabular}{c c} \hline \hline
**Main Classes of the Methods for the TL-ERT Data** & **List of the Papers** \\ \hline Joint-inversion with other geophysical data and & \begin{tabular}{c} [PERSON] et al., 2010 \\ [PERSON] et al., 2013 \\ [PERSON] et al., 2013 \\ [PERSON] et al., 2015 \\ \end{tabular} \\ \hline Full 4D inversion, time and space active constraints, space & \begin{tabular}{c} [PERSON] et al., 2011 \\ [PERSON] et al., 2011 \\ [PERSON] et al., 2011 \\ [PERSON] et al., 2014 \\ [PERSON] et al., 2015 \\ [PERSON] et al., 2016 \\ \end{tabular} \\ \hline Methods for minimizing the errors and the artifacts. & \begin{tabular}{c} [PERSON] et al., 2017 \\ [PERSON] et al., 2017 \\ [PERSON] et al., 2017 \\ [PERSON] et al., 2020 \\ \end{tabular} \\ \hline Clustering, Bayesian and other statistical approaches. & \
\begin{tabular}{c} [PERSON] et al., 2014 \\ [PERSON] et al., 2019 \\ [PERSON] et al., 2021 \\ \end{tabular} \\ \hline Open-source codes and HPC techniques. &
\begin{tabular}{c} [PERSON] et al., 2017 \\ [PERSON] et al., 2017 \\ [PERSON] et al., 2020 \\ [PERSON] et al., 2020 \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Simplified classification of the different approaches and methods adopted in the TL-ERT data processing and inversion. The scheme is based on the analysis of a selected list of papers published in the last ten years. [PERSON] et al., 2013 [77] investigated the complex geological environment of the Whitby Mudstone Formation, one of the highest landslide densities in the United Kingdom. They studied the landslide phenomena at Hollin Hill in North Yorkshire that includes shallow, retrogressive rotational, and translation movements. A permanent station able to perform time-lapse ERT observations was installed for monitoring the soil moisture pattern near the surface: the results allowed the authors to study the role of hydrogeological processes in triggering earth flows.