Advanced SBAS-DInSAR technique for controlling large civil infrastructures: an application to the Genzano di Lucania dam

Monitoring surface deformation on dams is commonly carried out by in situ geodetic surveying, which is time consuming and characterized by some limitations in space coverage and frequency. More recently microwave satellite-based technologies, such as advanced-DInSAR (Differential Synthetic Aperture Radar Interferometry), have allowed the integration and improvement of the observation capabilities of ground-based methods thanks to their effectiveness in collecting displacement measurements on many non-destructive control points, corresponding to radar reflecting targets. The availability of such a large number of points of measurement, which are distributed along the whole structure and are characterized by millimetric accuracy on displacement rates, can be profitably adopted for the calibration of numerical models. These models are implemented to simulate the structural behaviour of a dam under conditions of stress thus improving the ability to maintain safety standards. In this work, after having analysed how advanced DInSAR can effectively enhance the results from traditional monitoring systems that provide comparable accuracy measurements on a limited number of points, an FEM model of the Genzano di Lucania earth dam is developed and calibrated. This work is concentrated on the advanced DInSAR technique referred to as Small BAseline Subset (SBAS) approach, benefiting from its capability to generate deformation time series at full spatial resolution and from multi-sensor SAR data, to measure the vertical consolidation displacement of the Genzano di Lucania earth dam

A GeoNode-based platform for an effective exploitation of advanced DInSAR measurements

This work presents the development of an efficient tool for managing, visualizing, analysing, and integrating with other data sources, the deformation time-series obtained by applying the advanced differential interferometric synthetic aperture radar (DInSAR) techniques. To implement such a tool we extend the functionalities of GeoNode, which is a web-based platform providing an open source framework based on the Open Geospatial Consortium (OGC) standards, that allows development of Geospatial Information Systems (GIS) and Spatial Data Infrastructures (SDI). In particular, our efforts have been dedicated to enable the GeoNode platform to effectively analyze and visualize the spatio/temporal characteristics of the DInSAR deformation time-series and their related products. Moreover, the implemented multi-thread based new functionalities allow us to efficiently upload and update large data volumes of the available DInSAR results into a dedicated geodatabase. The examples we present, based on Sentinel-1 DInSAR results relevant to Italy, demonstrate the effectiveness of the extended version of the GeoNode platform

A user-oriented methodology for DInSAR time series analysis and interpretation: landslides and subsidence case studies

Recent advances in multi-temporal Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) have greatly improved our capability to monitor geological processes. Ground motion studies using DInSAR require both the availability of good quality input data and rigorous approaches to exploit the retrieved Time Series (TS) at their full potential. In this work we present a methodology for DInSAR TS analysis, with particular focus on landslides and subsidence phenomena. The proposed methodology consists of three main steps: (1) pre-processing, i.e., assessment of a SAR Dataset Quality Index (SDQI) (2) post-processing, i.e., application of empirical/stochastic methods to improve the TS quality, and (3) trend analysis, i.e., comparative implementation of methodologies for automatic TS analysis. Tests were carried out on TS datasets retrieved from processing of SAR imagery acquired by different radar sensors (i.e., ERS-1/2 SAR, RADARSAT-1, ENVISAT ASAR, ALOS PALSAR, TerraSAR-X, COSMO-SkyMed) using advanced DInSAR techniques (i.e., SqueeSAR™, PSInSAR™, SPN and SBAS). The obtained values of SDQI are discussed against the technical parameters of each data stack (e.g., radar band, number of SAR scenes, temporal coverage, revisiting time), the retrieved coverage of the DInSAR results, and the constraints related to the characterization of the investigated geological processes. Empirical and stochastic approaches were used to demonstrate how the quality of the TS can be improved after the SAR processing, and examples are discussed to mitigate phase unwrapping errors, and remove regional trends, noise and anomalies. Performance assessment of recently developed methods of trend analysis (i.e., PS-Time, Deviation Index and velocity TS) was conducted on two selected study areas in Northern Italy affected by land subsidence and landslides. Results show that the automatic detection of motion trends enhances the interpretation of DInSAR data, since it provides an objective picture of the deformation behaviour recorded through TS and therefore contributes to the understanding of the on-going geological processes

Automatic generation of co-seismic displacement maps by using Sentinel-1 interferometric SAR data

Abstract We present a tool for the automatic generation of co-seismic Differential Synthetic Aperture Radar Interferometry (DInSAR) products by using space-borne SAR data. In particular, the implemented tool relies on the large availability of Sentinel-1 SAR data and on-line earthquake catalogues (e.g. USGS, INGV) to generate co-seismic Line Of Sight (LOS) interferograms and displacement maps. The processing is triggered by the occurrence of a main seismic event, according to the accessible earthquake catalogues. The tool automatically retrieves all the needed SAR acquisitions that cover a defined area across the epicentre and generates the DInSAR products that will be then openly available through the European Plate Observing System (EPOS) portal. Moreover, the possibility to implement the presented tool into the upcoming Copernicus Data and Information Access Services (DIAS) will significantly reduce the product processing time, thus implying a faster product generation and delivery. Accordingly, such a tool not only will contribute to expand the use of DInSAR products in the geoscience field, but also will play a key role on the support of the Civil Protection authorities during the management of seismic crisis

Exploitation of large archives of ERS and ENVISAT C-band SAR data to characterize ground deformations

In the last few years, several advances have been made in the use of radar images to detect, map and monitor ground deformations. DInSAR (Differential Synthetic Aperture Radar Interferometry) and A-DInSAR/PSI (Advanced DInSAR/Persistent Scatterers Interferometry) technologies have been successfully applied in the study of deformation phenomena induced by, for example, active tectonics, volcanic activity, ground water exploitation, mining, and landslides, both at local and regional scales. In this paper, the existing European Space Agency (ESA) archives (acquired as part of the FP7-DORIS project), which were collected by the ERS-1/2 and ENVISAT satellites operating in the microwave C-band, were analyzed and exploited to understand the dynamics of landslide and subsidence phenomena. In particular, this paper presents the results obtained as part of the FP7-DORIS project to demonstrate that the full exploitation of very long deformation time series (more than 15 years) can play a key role in understanding the dynamics of natural and human-induced hazards. © 2013 by the authors

The Satellite Data Thematic Core Service within the EPOS Research Infrastructure

Trabajo presentado en la European Geosciences Union General Assembly, celebrada en Viena (Austria), del 23 al 28 de abril de 2017EPOS, the European Plate Observing System, is a long-term plan to facilitate the integrated use of data, data products, software and services, available from distributed Research Infrastructures (RI), for solid Earth science in Europe. Indeed, EPOS integrates a large number of existing European RIs belonging to several fields of the Earth science, from seismology to geodesy, near fault and volcanic observatories as well as anthropogenic hazards. The EPOS vision is that the integration of the existing national and trans-national research infrastructures will increase access and use of the multidisciplinary data recorded by the solid Earth monitoring networks, acquired in laboratory experiments and/or produced by computational simulations. The establishment of EPOS will foster the interoperability of products and services in the Earth science field to a worldwide community of users. Accordingly, the EPOS aim is to integrate the diverse and advanced European Research Infrastructures for solid Earth science, and build on new e-science opportunities to monitor and understand the dynamic and complex solid-Earth System. One of the EPOS Thematic Core Services (TCS), referred to as Satellite Data, aims at developing, implementing and deploying advanced satellite data products and services, mainly based on Copernicus data (namely Sentinel acquisitions), for the Earth science community. This work intends to present the technological enhancements, fostered by EPOS, to deploy effective satellite services in a harmonized and integrated way. In particular, the Satellite Data TCS will deploy five services, EPOSAR, GDM, COMET, 3D-Def and MOD, which are mainly based on the exploitation of SAR data acquired by the Sentinel-1 constellation and designed to provide information on Earth surface displacements. In particular, the planned services will provide both advanced DInSAR products (deformation maps, velocity maps, deformation time series) and value-added measurements (source model, 3D displacement maps, seismic hazard maps). Moreover, the services will release both on-demand and systematic products. The latter will be generated and made available to the users on a continuous basis, by processing each Sentinel-1 data once acquired, over a defined number of areas of interest; while the former will allow users to select data, areas, and time period to carry out their own analyses via an on-line platform. The satellite components will be integrated within the EPOS infrastructure through a common and harmonized interface that will allow users to search, process and share remote sensing images and results. This gateway to the satellite services will be represented by the ESA- Geohazards Exploitation Platform (GEP), a new cloud-based platform for the satellite Earth Observations designed to support the scientific community in the understanding of high impact natural disasters. Satellite Data TCS will use GEP as the common interface toward the main EPOS portal to provide EPOS users not only with data products but also with relevant processing and visualisation software, thus allowing users to gather and process on a cloud-computing infrastructure large datasets without any need to download them locallyPeer reviewe

MicroRNA 193b-3p as a predictive biomarker of chronic kidney disease in patients undergoing radical nephrectomy for renal cell carcinoma

Background: A significant proportion of patients undergoing radical nephrectomy (RN) for clear-cell renal cell carcinoma (RCC) develop chronic kidney disease (CKD) within a few years following surgery. Chronic kidney disease has important health, social and economic impact and no predictive biomarkers are currently available. MicroRNAs (miRs) are small non-coding RNAs implicated in several pathological processes. Methods: Primary objective of our study was to define miRs whose deregulation is predictive of CKD in patients treated with RN. Ribonucleic acid from formalin-fixed paraffin embedded renal parenchyma (cortex and medulla isolated separately) situated >3 cm from the matching RCC was tested for miR expression using nCounter NanoString technology in 71 consecutive patients treated with RN for RCC. Validation was performed by RT–PCR and in situ hybridisation. End point was post-RN CKD measured 12 months post-operatively. Multivariable logistic regression and decision curve analysis were used to test the statistical and clinical impact of predictors of CKD. Results: The overexpression of miR-193b-3p was associated with high risk of developing CKD in patients undergoing RN for RCC and emerged as an independent predictor of CKD. The addition of miR-193b-3p to a predictive model based on clinical variables (including sex and estimated glomerular filtration rate) increased the sensitivity of the predictive model from 81 to 88%. In situ hybridisation showed that miR-193b-3p overexpression was associated with tubule-interstitial inflammation and fibrosis in patients with no clinical or biochemical evidence of pre-RN nephropathy. Conclusions: miR-193b-3p might represent a useful biomarker to tailor and implement surveillance strategies for patients at high risk of developing CKD following RN

The psychological science accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data