Urban soils are unlike any others. Excavation, backfilling, sealing, compaction, demolition, and the importation of exogenous materials create intricate mosaics of soil horizons and anthropogenic deposits over very short distances. Physical and chemical properties such as texture, bulk density, porosity, organic matter content, pH, nutrient availability, and contaminant concentrations can change abruptly both laterally and vertically. Trace metals and organic pollutants inherited from former industrial activities, traffic emissions, and construction materials are frequently distributed in localized hotspots, further increasing spatial complexity. This heterogeneity challenges conventional soil sampling strategies, which often fail to adequately represent the spatial organization of soil properties and associated environmental constraints, making accurate characterization essential for land-use planning and avoiding inappropriate uses.

Over the past two decades, near-surface geophysical methods have become valuable tools for investigating soil spatial variability because they provide rapid, non-invasive, and spatially continuous information at resolutions that cannot be achieved through conventional sampling alone. Techniques including electromagnetic induction, ground-penetrating radar, seismic methods, and gamma-ray spectrometry respond to different physical properties of the subsurface, such as electrical conductivity, dielectric permittivity, seismic velocity, or natural radioactivity, which are themselves controlled by soil texture, water content, porosity, bulk density, clay mineralogy, soil structure, and the presence of coarse fragments or anthropogenic materials. Among these approaches, ERT has received particular attention because it provides high-resolution two- and three-dimensional images of the spatial distribution of subsurface electrical resistivity. The method is based on injecting electrical current into the ground and measuring the resulting potential differences, from which the true resistivity distribution is estimated through inversion procedures.

Soil electrical resistivity is governed by several interacting factors, including water content, pore connectivity, texture, clay mineralogy, porosity, and the abundance of coarse fragments or anthropogenic materials. Because electrical current is transmitted predominantly through the pore water rather than the solid mineral phase, bulk resistivity is controlled by the amount and composition of the pore water, pore connectivity, and the geometry of the pore network, all of which are strongly influenced by soil texture, structure, coarse fragment content, compaction, and horizon development. Consequently, resistivity integrates the effects of several key soil attributes and provides a physically meaningful representation of subsurface heterogeneity rather than direct measurements of individual soil properties. This integrative nature is particularly advantageous in urban environments, where soil variability often results from multiple superimposed processes that cannot easily be disentangled using conventional point measurements alone.

The study site was a plot of approximately 1,000 square meters located on the IRD site in Bondy, within the Seine-Saint-Denis department of the Paris metropolitan area. According to the land-use plan of the city of Bondy, the site lies over a succession of alluvial deposits derived from the 1:50,000-scale geological map produced by the French Geological Survey. Historically, the area was known in the mid-18th century for its dense forest, as shown in the 1756 Cassini map, and later became a popular destination for Parisians seeking rural retreats. The site was significantly altered during the construction of the IRD research center in 1947, when many gardens, vegetable plots, and refuse areas were consolidated, and the topography was substantially modified through the import and leveling of various materials, subsequently covered with a layer of forest-origin topsoil that was initially uncontaminated.

The ERT survey was carried out along linear profiles using a SYSCAL Pro resistivity meter operating quadrupoles sequentially selected among seventy-two electrodes. Measurements were performed using two electrode arrays: a reciprocal Wenner-Schlumberger configuration, which is well adapted to detect vertical contrasts in electrical resistivity and offers a better signal-to-noise ratio and greater depth of investigation, and a Dipole-Dipole configuration, which better captures horizontal contrasts and yields more pronounced resistivity contrasts at shallow depths. Short transverse profiles of 26.25 meters were spaced every 6 meters, while long longitudinal profiles of 53.25 meters were spaced every 1.5 meters, with a unit electrode spacing of 0.75 meters for both sets. The total number of measurements collected was 1,870 for the Dipole-Dipole array and 2,282 for the Wenner-Schlumberger array. Data interpretation was performed using RES2DINV and RES3DINV software, and spatial variation maps of calculated resistivity as a function of depth were generated using Surfer software.

The resistivity maps revealed significant variability both laterally and vertically. A linear anomaly observed at x = 5, extending down to approximately 90 centimeters depth, corresponded to a trench, with additional trench-like features visible near the center of the site radiating from a central manhole. At the surface, a first layer with resistivity around 50 ohm-meters corresponded to the topsoil layer distributed across the site. Below this, starting at approximately 25 centimeters depth, a second layer appeared with markedly lower resistivity values, indicative of coarse backfill material. In some areas, high-resistivity materials emerged with values reaching up to 315 ohm-meters, while at greater depths, intermediate resistivity zones of around 102 ohm-meters were detected in the southern and northeastern parts of the site, possibly corresponding to sandy pockets. The three-dimensional inversion enabled the generation of vertical resistivity profiles across the site with a spatial resolution of 37.5 by 37.5 square centimeters.

Two combined statistical analyses, Principal Component Analysis and Hierarchical Cluster Analysis, were used to classify all resistivity profiles by depth into four distinct groups, which served as the basis for the resulting classification map. While resistivity values were relatively similar across classes in the uppermost layer from 0 to 0.5 meters, they became highly discriminant between 0.5 and 2.5 meters depth. Class 1 showed both maximum and median resistivity values below 100 ohm-meters, whereas Class 4 reached a maximum resistivity exceeding 300 ohm-meters with median values around 220 ohm-meters. Classes 2 and 3 were intermediate, and Class 3 was notably distinct, characterized by a near-linear increase in resistivity with depth and high values beyond 2.5 meters. Following this typology, 30 auger surveys were distributed according to a proportionally stratified sampling design considering the surface area of each mapped resistivity unit, and soil samples were collected in each of the four soil categories at four different depths, totaling 120 samples.

The subsequent laboratory characterization showed that the ERT-derived classes corresponded to meaningful differences in measured soil characteristics. Soil texture was primarily controlled by depth, with only a weak effect of soil class, and the overall profiles exhibited a coarse texture with sand contents of 71 to 76 percent across layers. Classes C3 and C4 were relatively enriched in fine silt and clay, and significantly coarser textures occurred in layers B and C of soil class C4, which was also characterized by a relatively high sand content and low clay content in the surface layer. High concentrations of organic carbon and total nitrogen were observed in the surface layer corresponding to the added topsoil, with organic matter content decreasing markedly with depth to approximately tenfold lower organic carbon concentrations in the deepest layer. Both pH in water and pH in potassium chloride varied only with depth, showing an increase of approximately 0.5 pH units from the surface to the deepest layer, while cation exchange capacity, Olsen phosphorus, and most exchangeable cations were mainly driven by depth, positively correlated with soil organic carbon but negatively correlated with pH.

Mid-infrared spectroscopy revealed clear differences in organic matter composition among the ERT-derived classes, particularly for hydrophobic functional groups and polysaccharide-related compounds, suggesting that ERT may be more sensitive to qualitative differences in organic matter than to its total abundance. This interpretation is physically plausible because organic matter exerts a strong indirect control on soil electrical properties through its influence on aggregate stability, pore architecture, wettability, and water retention rather than through its intrinsic electrical conductivity. Hydrophobic organic compounds may reduce soil wettability and modify infiltration patterns, whereas microbial polysaccharides promote aggregate formation and enhance pore connectivity, thereby influencing the spatial distribution of soil water and the propagation of electrical current. Elemental composition determined by ICP-MS showed a strong and significant effect of depth for most elements, with significant differences among soil classes observed for several major elements including aluminum, iron, magnesium, and phosphorus, as well as for trace elements such as chromium and zinc. Trace elements, particularly lead, were detected at the site, but no significant differences among soil types were observed except in deeper layers, and variations in physico-chemical conditions, especially soil moisture, may influence trace element speciation and mobility, potentially affecting biota.

The findings carry broad implications for how cities understand the ground beneath them. Because the geoelectrical classes were established before soil sampling, the subsequent physicochemical measurements provided an independent assessment of whether the geophysical units corresponded to systematic differences in soil characteristics, and the significant differences observed when the physicochemical variables were considered jointly support the relevance of the spatial classification. ERT proved valuable not only for identifying spatial discontinuities but also for confirming the relative homogeneity of the site, thereby reducing uncertainty in soil characterization regardless of the degree of anthropogenic disturbance. The approach extends the use of ERT beyond conventional subsurface characterization by using continuous geophysical information as an operational decision-support tool for subsequent soil sampling, with broad potential applications including the optimization of soil quality and contamination monitoring programs, as well as the design of field experiments that account for pre-existing soil heterogeneity and thereby reduce experimental bias. Future studies should investigate the potential of time-lapse ERT, combined with complementary techniques such as electromagnetic induction, ground-penetrating radar, and digital soil mapping, to better characterize soil functioning, contaminant mobility, and temporal changes in urban environments, potentially opening new opportunities to investigate the links between soil structure, hydrological functioning, and carbon cycling in urban ecosystems.

Subject of Research: Urban soil science and geophysical characterization

Article Title: Exploring spatial variability in the physical and chemical properties of urban soils using electrical resistivity tomography

Article References: Ribler, C., Lerch, T. Z., & Robain, H. (2026). Exploring spatial variability in the physical and chemical properties of urban soils using electrical resistivity tomography. Frontiers in Soil Science, 6, Article 1924576. https://doi.org/10.3389/fsoil.2026.1924576

Image Credits: AI Generated

DOI: 10.3389/fsoil.2026.1924576

Keywords: electrical resistivity tomography, urban soils, soil sampling, organic matter, trace elements, geophysics, Exploring, spatial, variability, physical, chemical, properties