Remote Monitoring of Civil Infrastructure Based on TomoSAR

Structural health monitoring and damage detection tools are extremely important topics nowadays with the civil infrastructure aging and deteriorating problems observed in urban areas. These tasks can be done by visual inspection and by using traditional in situ methods, such as leveling or using traditional mechanical and electrical sensors, but these approaches are costly, labor-intensive and cannot be performed with a high temporal frequency. In recent years, remote sensing has proved to be a very promising methodology in evaluating the health of a structure by assessing its deformation and thermal dilation. The satellite-based Synthetic Aperture Radar Tomography (TomoSAR) technique, based on the exploitation of a stack of multi-temporal SAR images, allows to remotely sense the movement and the thermal dilation of individual structures with a centimeter-to millimeter-level accuracy, thanks to new generation high-resolution satellite-borne sensors. In this paper, the effectiveness of a recently developed TomoSAR technique in assessing both possible deformations and the thermal dilation evolution of man-made structures is shown. The results obtained using X-band SAR data in two case studies, concerning two urban structures in the city of Naples (Italy), are presented

Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel

Subsidence Detected by Multi-Pass Differential SAR Interferometry in the Cassino Plain (Central Italy): Joint Effect of Geological and Anthropogenic Factors?

In the present work, the Differential SAR Interferometry (DInSAR) technique has been applied to study the surface movements affecting the sedimentary basin of Cassino municipality. Two datasets of SAR images, provided by ERS 1-2 and Envisat missions, have been acquired from 1992 to 2010. Such datasets have been processed independently each other and with different techniques nevertheless providing compatible results. DInSAR data show a subsidence rate mostly located in the northeast side of the city, with a subsidence rate decreasing from about 5–6 mm/yr in the period 1992–2000 to about 1–2 mm/yr between 2004 and 2010, highlighting a progressive reduction of the phenomenon. Based on interferometric results and geological/geotechnical observations, the explanation of the detected movements allows to confirm the anthropogenic (surface effect due to building construction) and geological causes (thickness and characteristics of the compressible stratum

Analisi di dati DInSAR in aree urbane affette da subsidenza o frane a cinematica lenta

2012 - 2013Subsidence and slow-moving landslides systematically cause social, economic and environmental impacts all over the world. For this reason studies aimed at both the characterization of subsidence and slow-moving landslides and the analysis of the consequences on the exposed elements interacting with them are of great interest for the scientific and the technical community. These studies, to be useful in land use planning and management, need a huge number of displacement measurements within and on the boundary of the affected areas. Recently the scientific community has shownan increasing interest in the potential of using satellite observation techniques and, in particular, interferometric methods of Synthetic Aperture Radar (DInSAR)image processing. The literature review on DInSAR applications highlights the possibility of further researches pursuing the exploitation of DInSAR potentiality in studies at different scales and the development of procedures for the proper use of interferometric data and their validation with reference to well documented case studies. To this end, this PhD Thesis is aimed at developing original procedures for the analysis of the interferometric measurements specifically devotedto pursue two main objectives: the characterization of the phenomena of interest and the prediction of consequences to buildings interacting with them. The conceived procedures were tested, in sample areas of the Campania region (southern Italy)following a multi-scale approach. With reference to subsidence phenomena, the studies at small-scale involved the entire region and were mainly aimedatdetecting subsiding macro-areas; within these latter, more detailed studies at medium scale were carried out and the most affected municipalities were individuated. At large scale,focusing on one of these municipalities, studies dealing with the analysis of parameters whose variation leadsto the generation of the damage were carried out. Finally, at the scale of the single building the interferometric data were interpretedaccording todamageability criteria adopted in engineering practice. As forslow-moving landslides, the joint use of interferometric measurements and damage surveysallowed the updating of landslide inventory maps at medium scale and the analysis of the consequencesthrough the generation of fragility and vulnerability curves within a test area including 21 municipalities of BeneventoProvince. At large-scale studies were performed on a landslide-affected area within the municipality of Ascea(Salerno Province) in order to follow the evolution - in space and time - of the analyzed phenomenon as well as to deepen its kinematic behavior, in turn useful for zoning purposes. The obtained results highlight that the conceived procedures can valuably integrate the current practice for land use planning and as well as for the selection of the most suitablemanagement strategy.XII n.s

Environmental monitoring: landslide assessment and risk management (Test site: Vernazza, Cinque Terre Natural Park)

Natural disasters, whether of meteorological origin such as cyclones, floods, tornadoes and droughts or having geological nature such as earthquakes, volcanoes and landslide, are well known for their devastating impacts on human life, economy and environment. Over recent decades, the people and the societies are becoming more vulnerable; although the frequency of natural events may be constant, human activities contribute to their increased intensity. Indeed, every year millions of people are affected by natural disasters globally and, only in the last decade, more than 80% of all disaster-related deaths were caused by natural hazards. The PhD work is part of the activities for the support and development of methodologies useful to improve the management of environmental emergencies. In particular, it focused on the analysis of environmental monitoring and disaster risk management, a systematic approach to identify, to assess and to reduce the potential risks produced by a disaster. This method (Disaster Risk Management) aims to reduce socio-economic vulnerabilities and deals with natural and man-made events. In the PhD thesis, in particular, the slope movements have been evaluated. Slope failures are generally not so costly as earthquakes or major floods, but they are more widespread, and over the years may cause more property loss than any other geological hazard. In many developing regions slope failures constitute a continuing and serious impact on the social and economic structure. Specifically, the Italian territory has always been subject to instability phenomena, because of the geological and morphological characteristic and because of "extreme" weather events that are repeated more frequently than in the past, in relation to climate change. Currently these disasters lead to the largest number of victims and damages to settlements, infrastructure and historical and cultural environmental, after the earthquakes. The urban development, especially in recent decades, resulted in an increase of the assets at risk and unstable areas, often due to constant human intervention badly designed that led to instability also places previously considered "safe". Prevention is therefore essential to minimize the damages caused by landslides The objectives of the conducted research were to investigate the different techniques and to check their potentiality, in order to evaluate the most appropriate instrument for landslide hazard assessment in terms of better compromise between time to perform the analysis and expected results. The attempt is to evaluate which are the best methodologies to use according to the scenario, taking into consideration both reachable accuracies and time constraints. Careful considerations will be performed on strengths, weaknesses and limitations inherent to each methodology. The characteristics associated with geographic, or geospatial, information technologies facilitate the integration of scientific, social and economic data, opening up interesting possibilities for monitoring, assessment and change detection activities, thus enabling better informed interventions in human and natural systems. This is an important factor for the success of emergency operations and for developing valuable natural disaster preparedness, mitigation and prevention systems. The test site was the municipality of Vernazza, which in October 2011 was subject to a extreme rainfall which led to the occurrence of a series of landslides along the Vernazzola stream, which have emphasized the flood event that affected the water cours

Environmental monitoring: landslide assessment and risk management (Test site: Vernazza, Cinque Terre Natural Park)

Natural disasters, whether of meteorological origin such as cyclones, floods, tornadoes and droughts or having geological nature such as earthquakes, volcanoes and landslide, are well known for their devastating impacts on human life, economy and environment. Over recent decades, the people and the societies are becoming more vulnerable; although the frequency of natural events may be constant, human activities contribute to their increased intensity. Indeed, every year millions of people are affected by natural disasters globally and, only in the last decade, more than 80% of all disaster-related deaths were caused by natural hazards. The PhD work is part of the activities for the support and development of methodologies useful to improve the management of environmental emergencies. In particular, it focused on the analysis of environmental monitoring and disaster risk management, a systematic approach to identify, to assess and to reduce the potential risks produced by a disaster. This method (Disaster Risk Management) aims to reduce socio-economic vulnerabilities and deals with natural and man-made events. In the PhD thesis, in particular, the slope movements have been evaluated. Slope failures are generally not so costly as earthquakes or major floods, but they are more widespread, and over the years may cause more property loss than any other geological hazard. In many developing regions slope failures constitute a continuing and serious impact on the social and economic structure. Specifically, the Italian territory has always been subject to instability phenomena, because of the geological and morphological characteristic and because of "extreme" weather events that are repeated more frequently than in the past, in relation to climate change. Currently these disasters lead to the largest number of victims and damages to settlements, infrastructure and historical and cultural environmental, after the earthquakes. The urban development, especially in recent decades, resulted in an increase of the assets at risk and unstable areas, often due to constant human intervention badly designed that led to instability also places previously considered "safe". Prevention is therefore essential to minimize the damages caused by landslides The objectives of the conducted research were to investigate the different techniques and to check their potentiality, in order to evaluate the most appropriate instrument for landslide hazard assessment in terms of better compromise between time to perform the analysis and expected results. The attempt is to evaluate which are the best methodologies to use according to the scenario, taking into consideration both reachable accuracies and time constraints. Careful considerations will be performed on strengths, weaknesses and limitations inherent to each methodology. The characteristics associated with geographic, or geospatial, information technologies facilitate the integration of scientific, social and economic data, opening up interesting possibilities for monitoring, assessment and change detection activities, thus enabling better informed interventions in human and natural systems. This is an important factor for the success of emergency operations and for developing valuable natural disaster preparedness, mitigation and prevention systems. The test site was the municipality of Vernazza, which in October 2011 was subject to a extreme rainfall which led to the occurrence of a series of landslides along the Vernazzola stream, which have emphasized the flood event that affected the water course

Geomechanics of subsurface water withdrawal and injection

Land subsidence and uplift, ground ruptures, and induced seismicity are the principal geomechanic effects of groundwater withdrawal and injection. The major environmental consequence of groundwater pumping is anthropogenic land subsidence. The first observation concerning land settlement linked to subsurface processes was made in 1926 by the American geologists Pratt and Johnson, who wrote that \u2018\u2018the cause of subsidence is to be found in the extensive extraction of fluid from beneath the affected area.\u2019\u2019 Since then, impressive progress has been made in terms of: (a) recognizing the basic hydrologic and geomechanic principles underlying the occurrence; (b) measuring aquifer compaction and ground displacements, both vertical and horizontal; (c) modeling and predicting the past and future event; and (d) mitigating environmental impact through aquifer recharge and/or surface water injection. The first milestone in the theory of pumped aquifer consolidation was reached in 1923 by Terzaghi, who introduced the principle of \u2018\u2018effective intergranular stress.\u2019\u2019 In the early 1970s, the emerging computer technology facilitated development of the first mathematical model of the subsidence of Venice, made by Gambolati and Freeze. Since then, the comprehension, measuring, and simulation of the occurrence have improved dramatically. More challenging today are the issues of ground ruptures and induced/triggered seismicity, which call for a shift from the classical continuum approach to discontinuous mechanics. Although well known for decades, anthropogenic land subsidence is still threatening large urban centers and deltaic areas worldwide, such as Bangkok, Jakarta, and Mexico City, at rates in the order of 10 cm/yr

Detection of Partially Structural Collapse Using Long‐Term Small Displacement Data from Satellite Images

The development of satellite sensors and interferometry synthetic aperture radar (InSAR) technology has enabled the exploitation of their benefits for long‐term structural health monitoring (SHM). However, some restrictions cause this process to provide a small number of images leading to the problem of small data for SAR‐based SHM. Conversely, the major challenge of the long‐term monitoring of civil structures pertains to variations in their inherent properties by environmental and/or operational variability. This article aims to propose new hybrid unsupervised learning methods for addressing these challenges. The methods in this work contain three main parts: (i) data augmentation by the Markov Chain Monte Carlo algorithm, (ii) feature normalization, and (iii) decision making via Mahalanobis‐squared distance. The first method presented in this work develops an artificial neural network‐based feature normalization by proposing an iterative hyperparameter selection of hidden neurons of the network. The second method is a novel unsupervised teacher– student learning by combining an undercomplete deep neural network and an overcomplete single-layer neural network. A small set of long‐term displacement samples extracted from a few SAR images of TerraSAR‐X is applied to validate the proposed methods. The results show that the methods can effectively deal with the major challenges in the SAR‐based SHM applications