Giovanni Milillo

Monitoring dam structural health from space: Insights from novel InSAR techniques and multi-parametric modeling applied to the Pertusillo dam Basilicata, Italy

Abstract The availability of new constellations of synthetic aperture radar (SAR) sensors is leading to important advances in infrastructure monitoring. These constellations offer the advantage of reduced revisit times, providing low-latency data that enable analysis that can identify infrastructure instability and dynamic deformation processes. In this paper we use COSMO-SkyMed (CSK) and TerraSAR-X (TSX) data to monitor seasonal induced deformation at the Pertusillo dam (Basilicata, Italy) using multi-temporal SAR data analysis. We analyzed 198 images spanning 2010–2015 using a coherent and incoherent PS approach to merge COSMO-SkyMed adjacent tracks and TerraSAR-X acquisitions, respectively. We used hydrostatic-seasonal-temporal (HST) and hydrostatic-temperature-temporal (HTT) models to interpret the non-linear deformation at the dam wall using ground measurements together with SAR time-series analysis. Different look geometries allowed us to characterize the horizontal deformation field typically observed at dams. Within the limits of our models and the SAR acquisition sampling we found that most of the deformation at the Pertusillo dam can be explained by taking into account only thermal seasonal dilation and hydrostatic pressure. The different models show slightly different results when interpreting the aging term at the dam wall. The results highlight how short-revisit SAR satellites in combination with models widely used in the literature for interpreting pendulum and GPS data can be used for supporting structural health monitoring and provide valuable information to ground users directly involved in field measurements.

Space geodetic monitoring of engineered structures: The ongoing destabilization of the Mosul dam, Iraq

We present a detailed survey of the ongoing destabilization process of the Mosul dam. The dam is located on the Tigris river and is the biggest hydraulic structure in Iraq. From a geological point of view the dam foundation is poor due to a site geology formed by alternating strata of highly soluble materials including gypsum, anhydrite, marl and limestone. Here we present the first multi-sensor cumulative deformation map for the dam generated from space-based interferometric synthetic aperture radar measurements from the Italian constellation COSMO-SkyMed and the European sensor Sentinel-1a over the period 2014–2016 that we compare to an older dataset spanning 2004–2010 acquired with the European Envisat satellite. We found that deformation was rapid during 2004–2010, slowed in 2012–2014 and increased since August 2014 when grouting operations stopped due to the temporary capture of the dam by the self proclaimed Islamic State. We model the inferred deformation using a Markov chain Monte Carlo approach to solve for change in volume for simple tensile dislocations. Results from recent and historical geodetic datasets suggests that the volume dissolution rate remains constant when the equivalent volume of total concrete injected during re-grouting operations is included in the calculations.

Multi-Temporal InSAR Structural Damage Assessment: The London Crossrail Case Study

Spaceborne multi-temporal interferometric synthetic aperture radar (MT-InSAR) is a monitoring technique capable of extracting line of sight (LOS) cumulative surface displacement measurements with millimeter accuracy. Several improvements in the techniques and datasets quality led to more effective, near real time assessment and response, and a greater ability of constraining dynamically changing physical processes. Using examples of the COSMO-SkyMed (CSK) system, we present a methodology that bridges the gaps between MT-InSAR and the relative stiffness method for tunnel-induced subsidence damage assessment. The results allow quantification of the effect of the building on the settlement profile. As expected the greenfield deformation assessment tends to provide a conservative estimate in the majority of cases (~71% of the analyzed buildings), overestimating tensile strains up to 50%. With this work we show how these two techniques in the field of remote sensing and structural engineering can be synergistically used to complement and replace the traditional ground based analysis by providing an extended coverage and a temporally dense set of data.

Extension of Wavenumber Domain Focusing for spotlight COSMO-SkyMed SAR Data

Abstract In this work we describe a method to handle curved orbits in wavenumber domain focusing algorithm for high-resolution SAR data acquired by Low Earth Orbit satellites using spotlight mode. The standard wavenumber domain focusing algorithm make assumptions that start to be invalid when applied to high-resolution spotlight SAR data acquired in spaceborne low Earth orbit (LEO) configurations. The assumption of a hyperbolic range history is no longer accurate for sub-metric spatial resolutions due to the satellite curved orbit. The proposed method is used to estimate the satellite velocity and closest-approach range distance of the rectified effective orbit which minimizes the phase errors over the whole scene coverage. This allows to use all frequency domain focusing kernels developed to focus SAR images acquired with a stripmap mode. We use this method with the ω- k algorithm, and its approximation Fast ω-k (Fω-k), demonstrating its effectiveness to focus COSMO-SkyMed (CSK) SAR images obtaining, respectively, sub-metric and metric azimuth spatial resolution.

SAR images co-registration parallel implementation

Image co-registration is basilar for interferometry SAR remote sensing applications. This paper describes a parallel implementation based on the Farm skeleton using the MPI library for the co-registration module of SAR Toolbox software.

Analysis of algorithms for SAR data processing: an approach in the time domain

Time domain SAR data processing will probably be needed in future precision applications with data obtained in non standard SAR configurations (SCANSAR, STRIPMAP, etc.). In this article we present a new timedomain algorithm with a solution that mitigates the high computational cost typically connected with standard pixel by pixel procedures. This work has been supported by the MIUR-FIRB GRID.IT project no. RBNE01KNFP

Structural health monitoring of engineered structures using a space-borne synthetic aperture radar multi-temporal approach: from cultural heritage sites to war zones

Structural health monitoring (SHM) of engineered structures consists of an automated or semi-automated survey system that seeks to assess the structural condition of an anthropogenic structure. The aim of an SHM system is to provide insights into possible induced damage or any inherent signals of deformation affecting the structure in terms of detection, localization, assessment, and prediction. During the last decade there has been a growing interest in using several remote sensing techniques, such as synthetic aperture radar (SAR), for SHM. Constellations of SAR satellites with short repeat time acquisitions permit detailed surveys temporal resolution and millimetric sensitivity to deformation that are at the scales relevant to monitoring large structures. The all-weather multi-temporal characteristics of SAR make its products suitable for SHM systems, especially in areas where in situ measurements are not feasible or not cost effective. To illustrate this capability, we present results from COSMO-SkyMed (CSK) and TerraSAR-X SAR observations applied to the remote sensing of engineered structures. We show how by using multiple-geometry SAR-based products which exploit both phase and amplitude of the SAR signal we can address the main objectives of an SHM system including detection and localization. We highlight that, when external data such as rain or temperature records are available or simple elastic models can be assumed, the SAR-based SHM capability can also provide an interpretation in terms of assessment and prediction. We highlight examples of the potential for such imaging capabilities to enable advances in SHM from space, focusing on dams and cultural heritage areas.

Accuracy of high resolution CSK interferometric Digital Elevation Models

The accuracy of COSMO-SkyMed DEMs is investigated using StripMap mode images, acquired during the interferometric Tandem-Like mission characterized by a temporal baseline of 24 hours and spatial baselines maintained around 150-200 m. Some Couples of both Ascending and Descending interferometric pairs, acquired on selected test sites located in the California have been processed using the open source Delft Object-oriented Radar Interferometric Software (DORIS) and CSK DEMs with 10m posting generated. The validation has been conducted comparing CSK DEMs with more accurate DEMs (IfSar Coastal southern California DEMs). DEMANAL software, developed by prof. K. Jacobsen of the Leibniz University of Hannover, has been used for validation. Atmospheric effects have been removed using an auxiliary low-resolution height data (SRTM90). Ascending and Descending pass images on rough area have been fused in order to enhance the DEM quality. Results show a reduction in number of invalid pixels after fusion.

Quantitative analysis of stripmap and spotlight SAR interferometry with COSMO-SkyMed constellation

This work is focused on the phase validation of interferograms obtained by combining COSMO-SkyMed SAR images acquired by a single satellite (temporal baseline coincident with the orbital repeat cycle) or even by two satellites of the SAR constellation in equi-phased configuration on the orbital plane (temporal baseline: 8 days), thus minimizing the temporal decorrelation. Both qualitative and quantitative analyses have been therefore carried out for HI (HIMAGE: stripmap, single polarization) and S2 (enhanced spotlight) imaging modes, in order to proof whether or not COSMO-SkyMed constellation is well suited for SAR interferometry.

COSMO-SkyMed SAR processing parallel implementation

COSMO-SkyMed constellation will acquire data from its four SAR satellites in several image modes, and will generate focused data products. As images will be acquired at fine geometric resolution and will cover medium sized swath, the SAR processing involved will result well suited to parallel programming implementation.