Transport infrastructure monitoring by data fusion of GPR and SAR imagery information

Tosti, Fabio; Gagliardi, Valerio; D’Amico, Fabrizio; Alani, Amir M.

doi:10.1016/j.trpro.2020.02.097

Cited by 45 publications

(24 citation statements)

References 19 publications

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“…This is more evident in rural environment where roads, railways and runways can typically generate numerous PSs. Several applications of PSI related to the transport infrastructure monitoring can be found in the literature, such as [8][9][10][11][12][13][14][15], confirming its applicability to this area of endeavour.…”

Section: Psi For Transport Infrastructure Monitoringmentioning

confidence: 91%

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

Gagliardi

Ciampoli

D’Amico

et al. 2020

2020 IEEE Radar Conference (RadarConf20)

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Section: Psi For Transport Infrastructure Monitoringmentioning

confidence: 91%

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

Gagliardi

Ciampoli

D’Amico

et al. 2020

2020 IEEE Radar Conference (RadarConf20)

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“…In the last few years, several MT-InSAR techniques (i.e., InSAR [ 26 , 27 ], Small Baseline Subset (SBAS) [ 24 , 25 , 26 , 27 , 28 ], SqueeSAR [ 25 ]) relying on different approaches for the detection of PS targets (i.e., coherence, or amplitude stability index based), have been used for the monitoring of transport infrastructures, such as railways, highways, [ 35 , 36 , 37 , 38 , 39 ], bridges, tunnels [ 40 , 41 , 42 , 43 , 44 , 45 , 46 ], and airport runways [ 47 , 48 ].…”

Section: Displacement Monitoring Techniques and Data-analysis Methods For Airport Infrastructure Management: Background And Open Issuesmentioning

confidence: 99%

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

Gagliardi

Ciampoli

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).

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“…Benefits of this integrated approach is demonstrated by several past research applications [106], [118], [119] that have demonstrated the effectiveness of the coupled use of the InSAR technology and GPR method. The findings from these studies suggest that the integrated approach can correctly characterise the railway ballast deterioration.…”

Section: Benefits Of Network-level Satellite Remote Sensing and Ndt Mmentioning

confidence: 99%

Non-Destructive Technologies for a Sustainable Assessment and Monitoring of Railway Infrastructures: A Focus on GPR and InSAR Methods

Ferrante

Ciampoli

Benedetto

et al. 2021

Preprint

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Health monitoring of ballast in railway infrastructures is crucial to assure structural stability and efficiency of the operations. To this extent, an efficient and sustainable management of maintenance is fundamental for asset managers in setting up strategic and effective action plans. Amongst the available methods to assess the conditions of railway infrastructures, non-destructive technologies (NDT) are gaining popularity due to their capability to overcome main drawbacks of traditional routine methods, such as digging trenches and visually inspect locations assumed as critical along the track. The present paper presents an overview of the use of the Ground Penetrating Radar (GPR) and the Interferometric Synthetic Aperture (InSAR) technologies for a sustainable monitoring of railway infrastructures. Specifically, main traditional and non-destructive methods used for maintenance of railway ballast materials are presented with a special focus on their sustainability. A review about the research methods on the use of GPR and InSAR technologies for railway infrastructures also reported, including main investigations carried out in the laboratory and the real-life environments. Furthermore, a conceptual framework based on an integrated approach including satellite-based and ground-based investigations is proposed, where network and local level information can be merged for the detection of critical sections and the implementation of a more advanced predictive maintenance system.

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Transport infrastructure monitoring by data fusion of GPR and SAR imagery information

Cited by 45 publications

References 19 publications

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

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

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

Non-Destructive Technologies for a Sustainable Assessment and Monitoring of Railway Infrastructures: A Focus on GPR and InSAR Methods

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