In recent years, remote sensing technology has increasingly integrated various research fields. Among them, Synthetic Aperture Radar (SAR) is a powerful technique that can be used to monitor surface deformations and movements. This work investigates the possible effects of landslides insisting on a portion of a highway in Slovenia, mainly characterized by bridges and tunnels. This investigation spans two years and relies on Sentinel-1 SAR data, later validated with low-cost GNSS devices installed along the road. Regarding the SAR data, complex images from both ascending and descending orbits were collected; on these data, the Persistent Scatterer Interferometry (PSI) method was applied, obtaining the displacement time series for all the identified Persistent Scatterers (PS). After that, they were post-processed to separate the deterministic from the stochastic component of the motion and to model the behaviour of the highway elements. Finally, the correlation with the GNSS ground-truth data was exploited, getting results strongly dependent on the SAR viewing geometry. After validating the Sentinel-1 SAR processed data, the behaviour of different road components located on the road was investigated and compared to identify how different structures, such as retaining walls, roads, and bridges, behave differently. The results of this study contribute to improving the surveying of different road transportation infrastructures using remote sensing technologies.
Negli ultimi anni, la tecnologia del telerilevamento ha integrato sempre più vari campi di ricerca. Tra questi, il Radar ad Apertura Sintetica (SAR) è una tecnica potente che può essere utilizzata per monitorare le deformazioni e i movimenti superficiali. Questo lavoro indaga i possibili effetti delle frane su una parte di un’autostrada in Slovenia, principalmente caratterizzata da ponti e gallerie. L'indagine si estende su un periodo di due anni e si basa sui dati SAR di Sentinel-1, successivamente validati con dispositivi GNSS a basso costo installati lungo la strada. Per quanto riguarda i dati SAR, sono state raccolte immagini complesse da orbite ascendenti e discendenti; su questi dati è stato applicato il metodo PSI (Persistent Scatterer Interferometry), ottenendo la serie temporale degli spostamenti per tutti i Persistent Scatterers (PS) identificati. Successivamente, i dati sono stati post-elaborati per separare la componente deterministica da quella stocastica del movimento e per modellare il comportamento degli elementi dell’autostrada. Infine, è stata sfruttata la correlazione con i dati di verità a terra del GNSS, ottenendo risultati fortemente dipendenti dalla geometria di visualizzazione del SAR. Dopo aver validato i dati SAR di Sentinel-1 elaborati, è stato indagato e confrontato il comportamento di diversi componenti stradali situati lungo la strada per identificare come diverse strutture, come muri di contenimento, strade e ponti, si comportano diversamente. I risultati di questo studio contribuiscono a migliorare il rilevamento di diverse infrastrutture stradali utilizzando tecnologie di telerilevamento.
Highway deformation modelling from free Sentinel-1 SAR images in a landslide-susceptible region
Birinci, Ahmet Kaan
2023/2024
Abstract
In recent years, remote sensing technology has increasingly integrated various research fields. Among them, Synthetic Aperture Radar (SAR) is a powerful technique that can be used to monitor surface deformations and movements. This work investigates the possible effects of landslides insisting on a portion of a highway in Slovenia, mainly characterized by bridges and tunnels. This investigation spans two years and relies on Sentinel-1 SAR data, later validated with low-cost GNSS devices installed along the road. Regarding the SAR data, complex images from both ascending and descending orbits were collected; on these data, the Persistent Scatterer Interferometry (PSI) method was applied, obtaining the displacement time series for all the identified Persistent Scatterers (PS). After that, they were post-processed to separate the deterministic from the stochastic component of the motion and to model the behaviour of the highway elements. Finally, the correlation with the GNSS ground-truth data was exploited, getting results strongly dependent on the SAR viewing geometry. After validating the Sentinel-1 SAR processed data, the behaviour of different road components located on the road was investigated and compared to identify how different structures, such as retaining walls, roads, and bridges, behave differently. The results of this study contribute to improving the surveying of different road transportation infrastructures using remote sensing technologies.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/226418