High-resolution monitoring of landslides with UAS photogrammetry and digital image correlation

ABSTRACT

Periodically monitoring landslides is a key factor for supporting the realisation of hazard warning systems and risk reduction in the corresponding neighbourhood areas. Although satellite remote sensing solutions can be considered for low spatial resolution monitoring, this approach is still inappropriate for high spatial resolution investigations. Ground-based Radar Interferometry is also a widely used technique that allows for working at a proper spatial resolution, but it can often be an overbudget solution for most applications. Instead, photogrammetric surveys based on Unmanned Aerial System (UAS) imagery appear as a very interesting approach in terms of both spatial resolution and flexibility in temporally repeating the survey. Motivated by this observation, this work investigates the use of multi-temporal UAS surveys for landslide monitoring. To be more precise, Digital Image Correlation (DIC) has been applied to orthomosaics generated from different UAS photogrammetry surveys to compute the area’s deformation map. Compared with a reference GNSS survey, the results obtained using NHAZCA IRIS software and an in-house DIC approach show a deformation estimation accuracy of approximately 0.1 m, a reasonable accuracy for landslides moving at moderate velocity.

KEYWORDS:

• digital image correlation (DIC)
• unmanned aircraft system (UAS)
• GNSS
• deformation map
• monitoring

Acknowledgments

The authors would like to thank Dr. Giovanni Bertolini, Regione Emilia-Romagna - Agenzia per la Sicurezza Territoriale e Protezione Civile Servizio Sicurezza Territoriale e Protezione Civile di Reggio Emilia, Via Emilia Santo Stefano 25, 42100 Reggio Emilia; Prof. Alessandro Corsini, Dr. Marco Mulas, Dr. Giuseppe Ciccarese; Department of Chemical and Geological Sciences, Via Università 4, 41121 Modena; Prof. Grazia Tucci, Department of Civil and Environmental Engineering, University of Florence, via di S. Marta, 3 - 50139 Firenze, Italy.

The authors want to thank NHAZCA in a special way, for making the IRIS software available to perform the presented tests and for giving the necessary support (https://www.nhazca.it/).

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

Data are available on request from the authors. The data that support the findings of this study are available from the corresponding author [Mugnai F.] upon reasonable request (https://drive.google.com/drive/folders/1EfSI1VtoWHugYD5XWCK8MvTtbkMZzvJ2?usp=sharing).

Additional information

Funding

This research received no external funding