Résumé
<p>Over the last decade, many Electrical Resistivity Tomography (ERT) surveys have been acquired on landslides, both from surface and boreholes. The surveys aimed at inferring the geometry of the landslide body, at imaging conductive and resistive structures possibly linked to in-depth water storage, and even at qualifying underground water flows. Several ERT galvanic-type configurations have been deployed according to the sites, all of them using buried metallic electrodes as conductors. Devices were deployed both on hard rocks (mostly crystalline) and soft rock (mostly clayey) landslides, and most were associated with hydrogeological observations (soil temperature, groundwater table, soil humidity). <br>The acquired time-lapse resistivity profiles represent real added-value information for the long-term understanding of landslide processes and their links to meteorological and hydrological triggering factors. In France, most of the ERT surveys on landslides were acquired by the French Landslide Observatory (OMIV) of the Institute of Earth and Universe Science (INSU), in collaboration with many Universities (Strasbourg, Nice, Montpellier) and with the Geological Survey of Austria (Vienna). <br>The electrical resistivity datasets are acquired either individually on particular dates with possible repeated measurements or at high-frequency with fixed and automated measurement devices and permanent arrays. At the surface, multi-electrode ERT surveys are recorded by SYSCAL Pro (Iris Instrument) or GEOMON4D resistivimeters (GSA / Supper et al., 2002). Using the GEOMON4D device, at least 2 measurements of resistance are performed daily (using multiple gradient array). The SYSCAL resistivity surveys are measured every day using a Wenner-Schlumberger array. In boreholes, dipole-dipole electrical soundings are recorded daily using an autonomous acquisition system (ImaGeau®) with inter-electrode spacings of one meter. <br>The objective of this work is to present the OMIV-ERT free online repository of electrical resistivity data. Data are provided at three interpretational levels: (i) raw data (Vn and In, level 0), (ii) filtered and computed apparent resistivity (level 1), and (iii) inverted data (resistivity model, level 2). The information system consists of a PostgreSQL/PostGIS spatial database, R and Python scripts for data pre-processing and integration in the database. The pyGIMLi (Rücker et al., 2017) library is interfaced with R scripts to invert the resistivity data (from level 1 to level 2). An R-shiny-based web interface for data visualization and download is accessible online. The OMIV-ERT database will permit analyses of relationships between measured resistivities and landslide conditions.</p>