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.

Localization of passive Radio-Frequency Identification (RFID) tags has been used to monitor landslide surface displacement since 5 years. This method, applied on slow displacements lower than 1cm per day, allows a high spatio-temporal resolution at a relatively low cost. With the feedback of the previous years, this paper proposes to summarize the various challenges encountered with the long-term outdoor RFID localization method, and presents data-processing solutions that were implemented to overcome these challenges. We propose a complex-smoothing unwrapping algorithm, a multi-frequency merging operation, as well as multi-tag and multi-antenna phase combining method. The concept of an unwrapping reference guide is presented and applied with groups of tags showing coherent displacements, or with absolute reference measurements. These approaches allow a higher data availability up to 38% for one site over multiple years, and a better phase unwrapping. Earth surface displacement monitoring with RFID proves to be a robust and accurate solution, with four equipped sites across France and Switzerland.

Passive Radio-Frequency Identification (RFID) has been used to monitor landslide displacement since approximately 5 years. This method allows soil displacement estimation at a high spatio-temporal resolution, and at a relatively low cost. In perspective of the previous years, this paper proposes to summarize the various challenges encountered with the long-term outdoor RFID localization method, and presents solutions that were implemented to overcome these challenges. Finally, displacement results from three monitored sites are shown in order to validate the implemented solutions.

Radio-Frequency Identification (RFID) shows great potential for earth-sciences applications, notably in landslide surface monitoring at high spatio-temporal resolution [1] with meteorological robustness [2]. Ten 865MHzRFID tags were deployed on part of a landslide and continuously moni-tored for 8 months by a station composed of 4 reader antennas. 2D rela-tive localization was performed using a Phase-of-Arrival approach [3], andcompared with optical reference measurements. The centimeter-scale ac-curacy of this technique was confirmed theoretically by developing a mea-surement model that includes multipath interference and system sensitiv-ity kernel. Although horizontal localization shows promising results, ver-tical displacement monitoring presents intrinsic error sources that greatlydecrease accuracy in this direction. This study confirms that 2D landslidedisplacement tracking is feasible at relatively low station and maintenancecost (Charlety et al.,2021, submitted).References[1] M. Le Breton, L. Baillet, E. Larose, E. Rey, P. Benech, D. Jongmans, F. Guy-oton, and M. Jaboyedoff, “Passive radio-frequency identification ranging, adense and weather-robust technique for landslide displacement monitoring,”Engineering geology, vol. 250, pp. 1–10, 2019.[2] M. Le Breton, L. Baillet, E. Larose, E. Rey, P. Benech, D. Jongmans, andF. Guyoton, “Outdoor uhf rfid: Phase stabilization for real-world appli-cations,” IEEE Journal of Radio Frequency Identification, vol. 1, no. 4,pp. 279–290, 2017

We investigated the use of passive RFID tags for subsurface localization in challenging environments such as vegetation and snow. A synthetic aperture radar (SAR)-based RFID system was developed, combining high-precision GNSS tracking with phase-based localization methods. Two cost functions were evaluated: a standard complex phasor correlation and a guided phase unwrapping approach. Validation experiments were conducted with tags buried under vegetation layers (hay, bark) and snow covers (dry snow, 1.8-meter-thick wet snowpack). Localization errors were consistently below 5 cm horizontally and 15 cm vertically, even under deep wet snow. The guided phase unwrapping method improved robustness in distorted signal environments at the expense of higher computation time. These results demonstrate the feasibility of passive RFID localization in real-world environmental conditions, opening new perspectives for remote sensing and monitoring applications.

The use of Radio-Frequency Identification (RFID) in Earth Sciences has been growing in the recent years, notably for landslide monitoring using phase-of-arrival localization schemes. In this article, an Extended Kalman Filtering approach is presented to exploit RFID phase data for landslide displacement monitoring. The filtering is based on a stochastic Langevin equation for the state-space model, introducing a heuristic coupling based on the mechanical continuity of the landslide material. This helps correct measurement biases and deal with missing data in the tracking of multiple tags. The Kalman state covariance matrix is a useful indicator of the tags localization quality. It can be exploited to discriminate true displacements from multipath-induced artifacts. Phase unwrapping is performed implicitly through the state model.