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

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

Joint exploitation of space-borne and ground-based multitemporal InSAR measurements for volcano monitoring: The Stromboli volcano case study

Abstract We present a joint exploitation of space-borne and ground-based Synthetic Aperture Radar Interferometry (InSAR) and Multi Temporal (MT) InSAR measurements for investigating the Stromboli volcano (Italy) deformation phenomena. In particular, we focus our analysis on three periods: a) the time interval following the 2014 flank eruption, b) the July–August 2019 eruption and c) the following post-eruptive phase. To do this, we take advantage from an unprecedented set of space-borne and ground-based SAR data collected from April 2015 up to November 2019 along two (one ascending and one descending) Sentinel-1 (S-1) tracks, as well as, in the same period, by two ground-based systems installed along the Sciara del Fuoco northern rim. Such data availability permitted us to first characterize the volcano long-term 3D deformation behavior of the pre-eruptive period (April 2015–June 2019), by jointly inverting the space-borne and ground-based InSAR measurements. Then, the GB-SAR measurements allowed us to investigate the sin-eruptive time span (3rd July 2019 – 30th August 2019) which revealed rapid deformation episodes (e.g. more than 30 mm/h just 2 min before the 3rd July 2019 explosion) associated with the eruptive activity, that cannot be detected with the weekly S-1 temporal sampling. Finally, the S-1 measurements permitted to better constrain the post 2019 eruption deformations (31st August 2019 – 5th November 2019), which are mainly located outside the GB-SAR sensed area. The presented results demonstrate the effectiveness of the joint exploitation of the InSAR measurements obtained through satellite and terrestrial SAR systems, highlighting their strong complementarity to map and interpret the deformation phenomena affecting volcanic areas

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

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

National geohazards mapping in Europe: interferometric analysis of the Netherlands

The launch of Copernicus, the largest Earth Observation program to date, is significant due to the regular, reliable and freely accessible data to support space-based geodetic monitoring of physical phenomena that can result in natural hazards. In this study, wide area interferometric synthetic aperture radar (InSAR) capability is demonstrated by processing 436 Copernicus Sentinel-1 C-Band SAR images (May 2015–May 2017) using the Intermittent Small Baseline Subset (ISBAS) method to produce a wide-area-map (WAM) covering the Netherlands and extending into neighbouring areas of Belgium and Germany. Ground deformation velocities from six interferometric stacks, containing over 19 million measurements, were mosaicked together to produce a seamless ISBAS-WAM over some 53,000 km2 achieving a ground coverage of 94%. The retrieval of low-resolution measurements over soft surfaces (i.e. agricultural fields, forests, semi-natural areas and wetlands) afforded by the ISBAS technique was crucial due the dominance of non-urban land cover. Across the WAM, the spatial distribution of deformations concurs with independent sources of data, such as previous persistent scatterer interferometry (PSI) deformation maps, models of subsidence and settlement susceptibility, and quantitatively with GPS measurements over the Groningen gas field. A statistical analysis of the velocities reveals that intermittently coherent measurements in rural areas can provide reliable, additional deformation information with a very high degree of confidence (5σ), much of which is spatially correlated to known deformation features associated with compressible soils, infrastructure, peat oxidation, oil and gas production, salt mining and underground and opencast mining.Remotely derived deformation products, with near complete spatial coverage, provide a powerful tool for mitigation and remediation against adverse geological conditions to help in the protection of assets, property and life. The ISBAS-WAM demonstrates that routine generation of such products on a continental scale is now theoretically achievable, given the recent establishment of the Copernicus programme and the development of state-of-the-art InSAR methods such as ISBAS

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

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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