Optical and Thermal Image Processing for Monitoring Rainfall Triggered Shallow Landslides: Insights from Analogue Laboratory Experiments

Author:

Cosentino Antonio12ORCID,Marmoni Gian Marco1ORCID,Fiorucci Matteo3ORCID,Mazzanti Paolo124ORCID,Scarascia Mugnozza Gabriele1,Esposito Carlo12ORCID

Affiliation:

1. Department of Earth Sciences, “Sapienza” University of Rome and CERI Research Centre for Geological Risks, P.le Aldo Moro 5, 00185 Rome, Italy

2. IntelligEarth S.r.l.—Start UP, “Sapienza” University of Rome, Via V. Bachelet n. 12, 00185 Rome, Italy

3. Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio 43, 03043 Cassino, Italy

4. Nhazca S.r.l.—Start UP, “Sapienza” University of Rome, Via V. Bachelet n. 12, 00185 Rome, Italy

Abstract

This study explores the innovative use of digital image processing (DIP) techniques, also named PhotoMonitoring, for analysing the triggering conditions of shallow landslides. The approach, based on the combination of optical and infrared thermographic imaging (IRT), was applied to a laboratory-scale slope, reproduced in a flume test apparatus. Three experiments were conducted to replicate rainfall-induced shallow landslides, applying change detection and digital image correlation analysis to both optical and thermal images. The method combines IRT’s ability to measure ground surface temperature changes with DIP’s capacity to track movement and displacement. Results showed the high reliability of the displacement time-series obtained through IRT-DIP with respect to the reference optical-DIP. The IRT-DIP technique also detects anomaly signals two minutes before landslide occurrence that can be regarded as a possible failure precursor. This study testifies to the potential of image analysis as a remote sensing technique, demonstrating the ability of DIP to capture the dynamics of shallow landslides, as well as the advantages of optical–IRT combinations to follow slope deformation processes during night-time. This approach, if properly adapted to real-scale scenarios, may contribute to a better understanding of landslide behaviour, improve landslide monitoring strategies, and promote more effective early warning systems (EWS).

Funder

Sapienza University of Rome project

European Union

DARA—Dipartimento per gli Affari Regionali e le Autonomie

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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