A Global Archive of Coseismic DInSAR Products Obtained Through Unsupervised Sentinel-1 Data Processing

We present an automatic and unsupervised tool for the systematic generation of Sentinel-1 (S1) differential synthetic aperture radar interferometry (DInSAR) coseismic products. In particular, the tool first retrieves the location, depth, and magnitude of every seismic event from interoperable online earthquake catalogs (e.g., the United States Geological Survey (USGS) and the Italian National Institute of Geophysics and Volcanology (INGV) and then, for significant (with respect to a set of selected thresholds) earthquakes, it automatically triggers the downloading of S1 data and their interferometric processing over the area affected by the earthquake. The automatic system we developed has also been implemented within a Cloud-Computing (CC) environment, specifically the Amazon Web Services, with the aim of creating a global database of DInSAR S1 coseismic products, which consist of displacement maps and the associated wrapped interferograms and spatial coherences. This information will progressively be made freely available through the European Plate Observing System (EPOS) Research Infrastructure, thus providing the scientific community with a large catalog of DInSAR data that can be helpful for investigating the dynamics of surface deformation in the seismic zones around the Earth. The developed tool can also support national and local authorities during seismic crises by quickly providing information on the surface deformation induced by earthquakes

Getting ready for the generation of a nationwide ground motion product for Great Britain using SAR dta stacks: feasibility, data volumes and perspectives

This paper discusses the feasibility of monitoring ground stability and motion across the entire British landmass using satellite InSAR techniques. The ERS-1/2 and ENVISAT archive data availability, topographic visibility and land cover constraints for multi-temporal InSAR techniques to succeed across Britain are analysed. Data volumes, hardware and software requirements for the generation of a nationwide InSAR product are discussed, with a view to both novel processing methods to extend InSAR across unfavourable land covers, and parallel and cloud computing systems to decrease InSAR processing time demands. The P-SBAS method implemented into ESA’s G-POD platform is tested for London and Newcastle using ERS-1/2 1992-2000 and ENVISAT 2002-2008 image stacks, revealing a decrease of the processing time demand from several days to only ~8 hours per image frame

An insight in cloud computing solutions for intensive processing of remote sensing data

The investigation of Earth's surface deformation phenomena provides critical insights into several processes of great interest for science and society, especially from the perspective of further understanding the Earth System and the impact of the human activities. Indeed, the study of ground deformation phenomena can be helpful for the comprehension of the geophysical dynamics dominating natural hazards such as earthquakes, volcanoes and landslide. In this context, the microwave space-borne Earth Observation (EO) techniques represent very powerful instruments for the ground deformation estimation. In particular, Small BAseline Subset (SBAS) is regarded as one of the key techniques, for its ability to investigate surface deformation affecting large areas of the Earth with a centimeter to millimeter accuracy in different scenarios (volcanoes, tectonics, landslides, anthropogenic induced land motions). The current Remote Sensing scenario is characterized by the availability of huge archives of radar data that are going to increase with the advent of Sentinel-1 satellites. The effective exploitation of this large amount of data requires both adequate computing resources as well as advanced algorithms able to properly exploit such facilities. In this work we concentrated on the use of the P-SBAS algorithm (a parallel version of SBAS) within HPC infrastructure, to finally investigate the effectiveness of such technologies for EO applications. In particular we demonstrated that the cloud computing solutions represent a valid alternative for scientific application and a promising research scenario, indeed, from all the experiments that we have conducted and from the results obtained performing Parallel Small Baseline Subset (P-SBAS) processing, the cloud technologies and features result to be absolutely competitive in terms of performance with in-house HPC cluster solution

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

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

InSAR-Based Early Warning Monitoring Framework to Assess Aquifer Deterioration

Aquifer surveillance is key to understanding the dynamics of groundwater reservoirs. Attention should be focused on developing strategies to monitor and mitigate the adverse consequences of overexploitation. In this context, ground surface deformation monitoring allows us to estimate the spatial and temporal distribution of groundwater levels, determine the recharge times of the aquifers, and calibrate the hydrological models. This study proposes a methodology for implementing advanced multitemporal differential interferometry (InSAR) techniques for water withdrawal surveillance and early warning assessment. For this, large open-access images were used, a total of 145 SAR images from the Sentinel 1 C-band satellite provided by the Copernicus mission of the European Space Agency. InSAR processing was carried out with an algorithm based on parallel computing technology implemented in cloud infrastructure, optimizing complex workflows and processing times. The surveillance period records 6-years of satellite observation from September 2016 to December 2021 over the city of Chillan (Chile), an area exposed to urban development and intensive agriculture, where ~80 wells are located. The groundwater flow path spans from the Andes Mountain range to the Pacific Ocean, crossing the Itata river basin in the Chilean central valley. InSAR validation measurements were carried out by comparing the results with the values of continuous GNSS stations available in the area of interest. The performance analysis is based on spatial analysis, time series, meteorological stations data, and static level measurements, as well as hydrogeological structure. The results indicate seasonal variations in winter and summer, which corresponds to the recovery and drawdown periods with velocities > −10 mm/year, and an aquifer deterioration trend of up to 60 mm registered in the satellite SAR observation period. Our results show an efficient tool to monitor aquifer conditions, including irreversible consolidation and storage capacity loss, allowing timely decision making to avoid harmful exploitation

Innovative Techniques for the Retrieval of Earth’s Surface and Atmosphere Geophysical Parameters: Spaceborne Infrared/Microwave Combined Analyses

With the advent of the first satellites for Earth Observation: Landsat-1 in July 1972 and ERS-1 in May 1991, the discipline of environmental remote sensing has become, over time, increasingly fundamental for the study of phenomena characterizing the planet Earth. The goal of environmental remote sensing is to perform detailed analyses and to monitor the temporal evolution of different physical phenomena, exploiting the mechanisms of interaction between the objects that are present in an observed scene and the electromagnetic radiation detected by sensors, placed at a distance from the scene, operating at different frequencies. The analyzed physical phenomena are those related to climate change, weather forecasts, global ocean circulation, greenhouse gas profiling, earthquakes, volcanic eruptions, soil subsidence, and the effects of rapid urbanization processes. Generally, remote sensing sensors are of two primary types: active and passive. Active sensors use their own source of electromagnetic radiation to illuminate and analyze an area of interest. An active sensor emits radiation in the direction of the area to be investigated and then detects and measures the radiation that is backscattered from the objects contained in that area. Passive sensors, on the other hand, detect natural electromagnetic radiation (e.g., from the Sun in the visible band and the Earth in the infrared and microwave bands) emitted or reflected by the object contained in the observed scene. The scientific community has dedicated many resources to developing techniques to estimate, study and analyze Earth’s geophysical parameters. These techniques differ for active and passive sensors because they depend strictly on the type of the measured physical quantity. In my P.h.D. work, inversion techniques for estimating Earth’s surface and atmosphere geophysical parameters will be addressed, emphasizing methods based on machine learning (ML). In particular, the study of cloud microphysics and the characterization of Earth’s surface changes phenomenon are the critical points of this work

InSAR Monitoring of Italian Coastline Revealing Natural and Anthropogenic Ground Deformation Phenomena and Future Perspectives

In this work, we use X and C-band SAR data provided by the COSMO-SkyMed and ENVISAT missions to detect and measure some ground deformation phenomena along six coastal areas of Italy. In particular, we exploit multi-temporal interferometric synthetic aperture radar (InSAR), i.e., small baseline subsets (SBAS) and interferometric point target analysis (IPTA) methods, to retrieve the deformation rate maps and time series for each investigated area. Multi-temporal InSAR analysis revealed local subsidence and uplifting effects in Ravenna Coastal Areas, Fiumicino, Campi Flegrei, Sibari Plain, Augusta Bay, and Taranto Gulf. Our work is meant as a demonstrator to show how InSAR-based analysis can provide a detailed understanding of the coastal hazards. Such analysis also opens up new monitoring scenarios such as the possibility of designing a near real-time surveillance service based on Sentinel-1 SAR data.Publishedid 31522T. Deformazione crostale attivaJCR Journa

Urban geo big data

The paper deals with the general presentation of the Urban GEO BIG DATA, a collaborative acentric and distributed Free and Open Source (FOS) platform consisting of several components: local data nodes for data and related service Web deploy; a visualization node for data fruition; a catalog node for data discovery; a CityGML modeler; data-rich viewers based on virtual globes; an INSPIRE metadata management system enriched with quality indicators for each dataset.Three use cases in five Italian cities (Turin, Milan, Padua, Rome, and Naples) are examined: 1) urban mobility; 2) land cover and soil consumption at different resolutions; 3) displacement time series. Besides the case studies, the architecture of the system and its components will be presented

Near Real-Time InSAR Deformation Time Series Estimation With Modified Kalman Filter and Sequential Least Squares

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