Publications
RFID, landslides and geophysics

Hi ! I am Mathieu Le Breton, from Grenoble, France. I'm working as applied scientist in the company Géolithe, a consulting firm on natural risks.  I am investigating methods to monitor the near-surface (landslides and snowpack) with passive geophysics and wireless passive sensors. Here are some research publications.

RFID sensing as accurate as the best sensors on the market, validated for an entire winter in freezing cold

RFID sensing as accurate as the best sensors on the market, validated for an entire winter in freezing cold

Passive radio-frequency identification (RFID) was recently used to monitor landslide displacement at a high spatio-temporal resolution but only measured 1D displacement. This study demonstrates the tracking of 2D displacements, using an array of antennas connected to an RFID interrogator. Ten tags were deployed on a landslide for 12 months and 2D relative localization was performed using a phase-of-arrival approach. A period of landslide activity was monitored through RFID and displacements were confirmed by reference measurements. The tags showed displacements of up to 1.2 m over the monitored period. The centimeter-scale accuracy of the technique was confirmed experimentally and theoretically for horizontal localization by developing a measurement model that included antenna and tag positions, as well as multipath interference. This study confirms that 2D landslide displacement tracking with RFID is feasible at relatively low instrumental and maintenance cost. 


Passive RFID used in geoscience for sensing rivers, coasts, landslides, soil, snow ...

Billions of Radio-Frequency Identification (RFID) passive tags are produced yearly to identify goods remotely. New research and business applications are continuously arising, including recently localization and sensing to monitor earth surface processes. Indeed, passive tags can cost 10 to 100 times less than wireless sensors networks and require little maintenance, facilitating years-long monitoring with ten's to thousands of tags. This study reviews the existing and potential applications of RFID in geosciences. The major and mature application today is the study of coarse sediment transport during floods or debris flows, using tags placed into pebbles. More recently, tag localization was used to monitor landslide displacement, with a centimetric accuracy. Sensing tags were used to detect a displacement threshold on unstable rocks, and to monitor the moisture or the temperature of the soil. Propagation-based sensing was applied to monitor the properties of a volume of snow. RFID sensors, available today, can be applied to monitor other parameters, such as the vibration of structures, the tilt of unstable boulders, the strain of a material, or the salinity of water. We discuss the key challenges for using RFID monitoring more broadly in geosciences: the use of unmanned aerial vehicles to collect data or localize tags, the increase in reading range and duration, the ability to use tags placed under ground, snow, water or vegetation, and the optimization of economical and environmental cost. As a pattern, passive RFID could fill a gap between wireless sensor networks and manual measurements, to collect data efficiently over large areas, during several years, at high spatial density and moderate cost. 

Listening to ground vibrations can provide insight on a landslide stability

Monitoring landslides is essential to understand their dynamics and to reduce the risk of human losses by raising warnings before a failure. A decade ago, a decrease of apparent seismic velocity was detected several days before the failure of a clayey landslide, that was monitored with the ambient noise correlation method. It revealed its potential to detect precursor signals before a landslide failure, which could improve early warning systems. To date, nine landslides have been monitored with this method, and its ability to reveal precursors before failure seems confirmed on clayey landslides. However three challenges remain for operational early-warning applications: to detect velocity changes both rapidly and with confidence, to account for seasonal and daily environmental influences, and to check for potential instabilities in measurements. The ability to detect a precursoryvelocity change requires to adapt the processing workflow to each landslide: the key factors are the filtering frequency, the correlation time window, and the choice of temporal resolution. Other optional processing steps are described, to better measure rapid velocity changes, improve signal-to-noise ratio, or estimate the measurement uncertainty. The velocity also fluctuates seasonally, by 1 to 6% on the reviewed landslide studies, due to environmental influences. This review reveals a linear trend between the amplitude of seasonal fluctuations and the filtering frequency over the 0.1–20 Hz range, encompassing both landslide and non-landslide studies. The environmental velocity fluctuations are caused mostly by groundwater levels and soil freezing/thawing, but could also be affected by snow height, air temperature and tide depending on the site. Daily fluctuations should also occur on landslides, and can be an issue when seeking to obtain a sub-daily resolution useful for early-warning systems. Finally, spurious fluctuations of apparent velocity—unrelated to the material dynamics—should be verified for. They can be caused by changes in noise sources (location or spectral content), in site response (change of scatterers, attenuation, or resonance frequency due to geometrical factors), or in inter-sensor distance. As a perspective, the observation of seismic velocity changes could contribute in assessing a landslide stability across time, both during the different creeping stages occurring before a potential failure, and during its reconsolidation after a failure.

RFID tags to monitor landslide in mountains

The first time an RFID monitoring system was deployed in mountain conditions on a landslide

How to make clean phase measurements on RFID tags, removing influence from water and temperature

This paper investigates meteorological factors that affect the phase of radio-frequency identification (RFID) passive tags at 868 MHz, in outdoor conditions. The study identifies the effect of water on the tag and base antennas, the effect of temperature on the cables, tags, and base antenna, the effect of thetag support moisture, and  the effect of atmospheric conditions on wave velocity. Combined, these effects could lead to over 8.1 radians phase drift over a year, in a typical environment. In a tag location tracking application, that would correspond to an error of 22 cm. This paper proposes techniques to correct these effects and to increase the phase stability. These techniques are applied to a new RFID system, which is tested in outdoor conditions, for five months. The new system improves the phase stability for rainy days, dry days, and long-term drift by a factor of 3, 12, and 5, respectively. After corrections, the long-term drift was reduced to below 0.05 radians per month, which corresponds to 1.5 millimeter per month.

Geoelectrical characterization of volcanic rocks (3/3)

Induced polarization is a geophysical method investigating the ability of rocks to store reversibly electrical charges under a slowly alternating electrical field. The material property of interest is a complex-valued electrical conductivity with an in-phase component associated with conduction and a quadrature component associated with polarization. We investigated the relationship between complex conductivity spectra over the frequency range 1 mHz–45 kHz and the specific surface area (SSA) of 28 volcanic core samples extracted from a wellbore drilled for the Humuʻula Groundwater Research Project in Hawaii. The specific surface area of these samples was determined through the Brunauer, Emmett and Teller (BET) method. Subcritical nitrogen adsorption experiments were conducted using two different instruments and the samples were prepared in both pellets and powder forms. The BET specific surface area is found to be highly correlated to the cation exchange capacity of the core samples measured by the cobalthexamine method. The in-phase conductivity itself can be decomposed as the sum of a bulk contribution associated with conduction in the bulk pore water and a surface conductivity associated with conduction in the electrical double layer coating the grains. The surface conductivity, the quadrature conductivity, and the normalized chargeability (defined as the difference between the in-phase conductivity at high and low frequencies) are observed to be linearly correlated to the specific surface area or the surface per volume ratio of the core samples, which can be considered as proxy of alteration. These trends are consistent with those shown by sedimentary rocks. This new data set demonstrates that the induced polarization method can be potentially used to image alteration in volcanic environments.

Geoelectrical characterization of volcanic rocks (2/3)

We investigate the relationship between complex conductivity spectra and both permeability and pore mean size and distribution of 22 core samples (21 volcanic rocks and 1 clayey sandstone). The volcanic core samples were extracted from a wellbore drilled for the Humu‘ula Groundwater Research Project in the Humu‘ula saddle region between Mauna Kea and Mauna Loa volcanoes (Hawaii). The quadrature conductivity spectra of volcanic rocks exhibit a subtle, but generally detectable, relaxation frequency in the range 0.3 Hz to 45 kHz similar to the relaxation frequency observed for clayey sandstones. We find a fair relationship between this relaxation frequency and the pore size determined by mercury porosimetry. Combined with the intrinsic formation factor of the core samples, the relaxation frequency can be used as an indicator of the permeability of the material. The predicted values of the permeability are grossly consistent with the permeability values to air (in the range 0.001–100 mD) within two orders of magnitude. The measured permeability values are highly correlated to the peak of the pore size distribution determined from mercury porosimetry divided by the intrinsic formation factor. By fitting the complex conductivity spectra with the pore size distribution, we obtain the normalized chargeability of the core samples, which is, in turn, highly correlated to the measured cation exchange capacity.

My first research work, on geoelectrical characterization of volcanic rocks (1/3)

We performed complex conductivity measurements on 28 core samples from the hole drilled for the Humu’ula Groundwater Research Project (Hawai’i Island, HI, USA). The complex conductivity measurements were performed at 4 different pore water conductivities (0.07, 0.5, 1.0 or 2.0, and 10 S m −1 prepared with NaCl) over the frequency range 1 mHz to 45 kHz at 22 ± 1◦ C. The in-phase conductivity data are plotted against the pore water conductivity to determine, sample by sample, the intrinsic formation factor and the surface conductivity.The intrinsic formation factor is related to porosity by Archie’s law with an average value of the cementation exponent m of 2.45, indicating that only a small fraction of the connected pore space controls the transport properties. Both the surface and quadrature conductivities are found to be linearly related to the cation exchange capacity of the material, which was measured with the cobalt hexamine chloride method. Surface and quadrature conductivities are found to be proportional to each other like for sedimentary siliclastic rocks. A Stern layer polarization model is used to explain these experimental results. Despite the fact that the samples contain some magnetite (up to 5 per cent wt.), we were not able to identify the effect of this mineral on the complex conductivity spectra. These results are very encouraging in showing that galvanometric induced polarization measurements can be used in volcanic areas to separate the bulk from the surface conductivity and therefore to define some alteration attributes. Such a goal cannot be achieved with resistivity alone.