Tracking morphological changes and slope instability using spaceborne and ground-based SAR data

Stromboli (Aeolian Archipelago, Italy) is an active volcano that is frequently affected by moderate to large mass wasting, which has occasionally triggered tsunamis. With the aim of understanding the relationship between the geomorphologic evolution and slope instability of Stromboli, remote sensing information from space-born Synthetic Aperture Radar (SAR) change detection and interferometry (InSAR) and Ground Based InSAR (GBInSAR) was compared with field observations and morphological analyses. Ground reflectivity and SqueeSAR⢠(an InSAR algorithm for surface deformation monitoring) displacement measurements from X-band COSMO-SkyMed satellites (CSK) were analysed together with displacement measurements from a permanent-sited, Ku-band GBInSAR system. Remote sensing results were compared with a preliminary morphological analysis of the Sciara del Fuoco (SdF) steep volcanic flank, which was carried out using a high-resolution Digital Elevation Model (DEM). Finally, field observations, supported by infrared thermographic surveys (IRT), allowed the interpretation and validation of remote sensing data. The analysis of the entire dataset (collected between January 2010 and December 2014) covers a period characterized by a low intensity of Strombolian activity. This period was punctuated by the occurrence of lava overflows, occurring from the crater terrace evolving downslope toward SdF, and flank eruptions, such as the 2014 event. The amplitude of the CSK images collected between February 22nd, 2010, and December 18th, 2014, highlights that during periods characterized by low-intensity Strombolian activity, the production of materials ejected from the crater terrace towards the SdF is generally low, and erosion is the prevailing process mainly affecting the central sector of the SdF. CSK-SqueeSAR⢠and GBInSAR data allowed the identification of low displacements in the SdF, except for high displacement rates (up to 1.5 mm/h) that were measured following both lava delta formation after the 2007 eruption and the lava overflows of 2010 and 2011. After the emplacement of the 2014 lava field, high displacements in the central and northern portions of the SdF were recorded by the GBInSAR device, whereas the spaceborne data were unable to detect these rapid movements. A comparison between IRT images and GBInSAR-derived displacement maps acquired during the same time interval revealed that the observed displacements along the SdF were related to the crumbling of newly emplaced 2014 lava and of its external breccia. Detected slope instability after the 2014 flank eruption was related to lava accumulation on the SdF and to the difference in the material underlying the 2014 lava flow: i) lava flows and breccia layers related to the 2002â03 and 2007 lava flow fields in the northern SdF sector and ii) loose volcaniclastic deposits in the central part of the SdF. This work emphasizes the importance of smart integration of spaceborne, SAR-derived hazard information with permanent-sited, operational monitoring by GBInSAR devices to detect areas impacted by mass wasting and volcanic activity

Railways' stability observed in Campania (Italy) by InSAR data

Campania region is characterized by intense urbanization, active volcanoes, subsidence, and landslides; therefore, the stability of public transportation structures is highly concerned. We have app..

Railways’ Stability Observation by Satellite Radar Images

Remote sensing has many vital civilian applications. Space-borne Interferometric Synthetic Aperture Radar has been used to measure the Earth’s surface deformation widely. In particular, Persistent Scatterer Interferometry (PSI) is designed to estimate the temporal characteristics of the Earth’s deformation rates from multiple InSAR images acquired over time. This chapter reviews the space-borne Differential Interferometric Synthetic Aperture Radar techniques that have shown their capabilities in monitoring of railways displacements. After description of the current state of the art and potentials of the available radar remote sensing techniques, one case study is examined, pertaining to a railway bridge in the Campania region, Italy

A Method for Selecting SAR Interferometric Pairs Based on Coherence Spectral Clustering

To achieve accurate interferometric synthetic aperture radar (SAR) phase estimation, it is essential to select appropriate high-coherence interferometric pairs from massive SAR single-look complex (SLC) image data. The selection should include as many high-coherence interferometric pairs as possible while avoiding low-coherence pairs. By combining coherence and spectral clustering, a novel selection method for SAR interferometric pairs is proposed in this article. The proposed method can be adopted to classify SAR SLC images into different clusters, where the total coherence of interferometric pairs in the same cluster is maximized while that among different clusters is minimized. This is implemented by averaging the coherence matrices of representative pixels to construct an adjacency matrix and performing eigenvalue decomposition for estimating the number of clusters. The effectiveness of the proposed method is demonstrated using 33 TerraSAR-X and 38 dual-polarization Sentinel-1A data samples, yielding improved topography and deformation monitoring results

Advanced interpretation of land subsidence by validating multi-interferometric SAR data: the case study of the Anthemountas basin (Northern Greece)

The potential of repeat-pass space borne SAR (Synthetic Aperture Radar) interferometry has been exploited to investigate spatial patterns of land subsidence in the Anthemountas basin, in the northern part of Greece. The PSI (Persistent Scatterer Interferometry) approach, based on the processing of long series of SAR acquisitions, has been applied to forty-two images acquired in 1995–2001 by ERS1/2 satellites. Interferometric results have been analysed at a basin scale as support for land motion mapping and at a local scale for the characterisation of ground motion events affecting the village of Perea in the Thermaikos municipality and the "Macedonia" international airport. PSI results revealed a moderate subsidence phenomenon along the wider coastal zone of Anthemountas basin corresponding to intense groundwater extraction. Highest values, exceeding −20 mm yr−1, were measured in the airport area where the thickest sequence of compressible Quaternary sediments occurs. Intense subsidence has been detected also in the Perea village (maximum deformation of −10 to −15 mm yr−1), where a series of fractures, causing damages to both buildings and infrastructure, occurred in 2005–2006

A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast

open20siThe Mediterranean region is frequently struck by severe rainfall events causing numerous casualties and several million euros of damages every year. Thus, improving the forecast accuracy is a fundamental goal to limit social and economic damages. Numerical Weather Prediction (NWP) models are currently able to produce forecasts at the km scale grid spacing but unreliable surface information and a poor knowledge of the initial state of the atmosphere may produce inaccurate simulations of weather phenomena. The STEAM (SaTellite Earth observation for Atmospheric Modelling) project aims to investigate whether Sentinel satellites constellation weather observation data, in combination with Global Navigation Satellite System (GNSS) observations, can be used to better understand and predict with a higher spatio-temporal resolution the atmospheric phenomena resulting in severe weather events. Two heavy rainfall events that occurred in Italy in the autumn of 2017 are studied—a localized and short-lived event and a long-lived one. By assimilating a wide range of Sentinel and GNSS observations in a state-of-the-art NWP model, it is found that the forecasts benefit the most when the model is provided with information on the wind field and/or the water vapor content.openLagasio, Martina; Parodi, Antonio; Pulvirenti, Luca; Meroni, Agostino N.; Boni, Giorgio; Pierdicca, Nazzareno; Marzano, Frank S.; Luini, Lorenzo; Venuti, Giovanna; Realini, Eugenio; Gatti, Andrea; Tagliaferro, Giulio; Barindelli, Stefano; Monti Guarnieri, Andrea; Goga, Klodiana; Terzo, Olivier; Rucci, Alessio; Passera, Emanuele; Kranzlmueller, Dieter; Rommen, BjornLagasio, Martina; Parodi, Antonio; Pulvirenti, Luca; Meroni, Agostino N.; Boni, Giorgio; Pierdicca, Nazzareno; Marzano, Frank S.; Luini, Lorenzo; Venuti, Giovanna; Realini, Eugenio; Gatti, Andrea; Tagliaferro, Giulio; Barindelli, Stefano; Monti Guarnieri, Andrea; Goga, Klodiana; Terzo, Olivier; Rucci, Alessio; Passera, Emanuele; Kranzlmueller, Dieter; Rommen, Bjor

Performance Improvement for SAR Tomography Based on Local Plane Model

Multilook approaches have been applied in synthetic aperture radar (SAR) tomography (TomoSAR), for improving the density and regularity of persistent scatterers reconstructed from multipass SAR images in both rural and urban regions. Multilook operations assume that all scatterers in a given neighborhood are similar in height, thereby providing additional data for recovering the position and reflectivity of a single scatterer, so that a higher signal-to-noise ratio can be achieved. This is equivalent to assuming that scatterers belonging to a local neighborhood of range-azimuth cells are located on horizontal planes. The present article generalizes this approach by adopting the so-called local plane (LP) model for TomoSAR imaging in urban areas, accounting for local variations in the height of scatterers that are not negligible. Furthermore, an LP-generalized likelihood ratio test (LP-GLRT) algorithm is developed to implement the previous idea. Compared with the multilook generalized likelihood ratio test algorithm, LP-GLRT shows better performance in the case of urban structures and terrains in experiments based on both simulated data and TerraSAR-X images