A novel geo-statistical approach for transport infrastructure network monitoring by Persistent Scatterer Interferometry (PSI)

Trevisani

et al. 2021

Sensors

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Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques are gaining momentum in the assessment and health monitoring of infrastructure assets. Amongst others, the Persistent Scatterers Interferometry (PSI) technique has proven to be viable for the long-term evaluation of ground scatterers. However, its effectiveness as a routine tool for certain critical application areas, such as the assessment of millimetre-scale differential displacements in airport runways, is still debated. This research aims to demonstrate the viability of using medium-resolution Copernicus ESA Sentinel-1A (C-Band) SAR products and their contribution to improve current maintenance strategies in case of localised foundation settlements in airport runways. To this purpose, “Runway n.3” of the “Leonardo Da Vinci International Airport” in Fiumicino, Rome, Italy was investigated as an explanatory case study, in view of historical geotechnical settlements affecting the runway area. In this context, a geostatistical study is developed for the exploratory spatial data analysis and the interpolation of the Sentinel-1A SAR data. The geostatistical analysis provided ample information on the spatial continuity of the Sentinel 1 data in comparison with the high-resolution COSMO-SkyMed data and the ground-based topographic levelling data. Furthermore, a comparison between the PSI outcomes from the Sentinel-1A SAR data—interpolated through Ordinary Kriging—and the ground-truth topographic levelling data demonstrated the high accuracy of the Sentinel 1 data. This is proven by the high values of the correlation coefficient (r = 0.94), the multiple R-squared coefficient (R2 = 0.88) and the Slope value (0.96). The results of this study clearly support the effectiveness of using Sentinel-1A SAR data as a continuous and long-term routine monitoring tool for millimetre-scale displacements in airport runways, paving the way for the development of more efficient and sustainable maintenance strategies for inclusion in next generation Airport Pavement Management Systems (APMSs).

“…Regardless of the specific acquisition geometry, the LoS displacement ( D los ) is a projection of a three-dimensional displacement vector [ 47 , 49 , 50 ]:

Section: Resultsmentioning

confidence: 99%

Testing Sentinel-1 SAR Interferometry Data for Airport Runway Monitoring: A Geostatistical Analysis

Trevisani

et al. 2021

Sensors

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“…The limited errors confirmed that PS-InSAR analyses of high frequency images are very effective in reconstructing vertical deformations in airfield runways. In [61], a novel geostatistical approach was developed to ease the postprocessing of large datasets of PSs resulting from the application of the PSI algorithms over an area of interest. The approach aims at correcting the component of the displacement collected from the acquisition geometry of the sensor (i.e., ascending and descending), and to increase the accuracy of measurements.…”

Section: Airfieldsmentioning

confidence: 99%

Integration of Remote Sensing and Ground-Based Non-Destructive Methods in Transport Infrastructure Monitoring: Advances, Challenges and Perspectives

Tosti

2021 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)

et al. 2021

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High temporal frequency monitoring of transport infrastructures is crucial for implementing effective maintenance prioritisation strategies and prevent major failures. To this extent, ground-based non-destructive testing (NDT) methods have been successfully applied for decades, reaching very high standards of data quality and accuracy. However, routine and systematic campaigns are required over relatively long inspection times for data collection and implementation into reliable infrastructure management systems (IMSs). On the other hand, satellite remote sensing techniques, such as the Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) method, have proven effective in monitoring ground displacements of transport infrastructures (roads, railways and airfields), with a much higher temporal frequency of investigation and wider inspection catchment areas. Nevertheless, the integration of information from i) satellite remote sensing and ii) ground-based NDT methods is still an area to be explored in civil engineering. Within this framework, this paper aims to review significant stand-alone applications in these two areas of technology for transport infrastructure monitoring. Furthermore, recent advances, main challenges and future perspectives arising from their integration are discussed. Contents of this paper are organised within the context of an invited keynote talk given at

“…Therefore, the displacement detected is a component of the real displacement that occurred on the ground. Different approaches were proposed to evaluate the real displacements-velocity-vector, from datasets acquired in different acquisition geometries (i.e., Ascending and Descending) [32,33]. For the investigated area of interest, SAR images in ascending acquisition geometries were used for both the Sentinel-1A and COSMO-SkyMed missions, in the observation period of this study.…”

Section: Psi Processingmentioning

confidence: 99%

Novel Perspectives in the Monitoring of Transport Infrastructures by Sentinel-1 and Cosmo-Skymed Multi-Temporal SAR Interferometry

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS

D’Amico

et al. 2021

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In recent years, successful applications of the Synthetic Aperture Radar Interferometry (InSAR) for the monitoring of subsidence and deformations in transport infrastructures have been reported in the literature. The main advantage of this technique compared to other non-destructive surveying methodologies is in the possibility to perform fast networklevel surveys as well as the provision of time-series of the displacements by multi-temporal data acquisitions. Given the medium ground resolution, C-band imagery are usually not employed for transport infrastructure monitoring as it is considered unlikely to obtain sufficiently accurate information. However, the use of medium resolution SAR data has not been thoroughly investigated until now and is still an open challenge. This study presents a novel approach for transport assets monitoring, based on the synergistic use of medium resolution (C-Band) and high resolution (X-Band) SAR imagery. To this effect, a multitemporal SAR Interferometry analysis of high and mediumresolution datasets is performed on a runway of the Leonardo Da Vinci Airport in Rome, Italy. The data were acquired by the Sentinel-1A and the COSMO-SkyMed missions, respectively. A comparison between the results from medium and high-resolution datasets demonstrates the viability of using multi-frequency SAR imagery, and pave the way to the development of new methodologies for the monitoring of transport infrastructures.