Fabiana Calò

An application of the SBAS-DInSAR technique for the assessment of structural damage in the city of Rome

The remote sensing technique known as Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) allows the detection and monitoring of ground settlements, by generating deformation velocity maps and displacement time-series having centimeter to millimeter accuracy. These measurements can contribute to the evaluation of the structural conditions of the constructions. Given the settlements, different approaches exist for the assessment of the structural damage, ranging from empirical estimates to detailed finite element calculations. In this work, we integrate the results of a DInSAR analysis with an intermediate semi-empirical model to investigate three buildings located in the southern part of the city of Rome. The model, originally proposed by Finno et al. [(2005). ASCEJournal of Geotechnical and Geoenvironmental Engineering, 131(10), 1199–1210], considers each building as an equivalent laminated beam, where the layers represent the floors and the core material reproduces the infill walls. The results obtained by the model have been compared to the damages observed on the buildings, showing a good agreement and demonstrating that the proposed approach represents an effective and, at the same time, simple assessment tool for rapidly evaluating the conditions of several structures.

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.

Integration of Optical and SAR Data for Burned Area Mapping in Mediterranean Regions

The aim of this paper is to investigate how optical and Synthetic Aperture Radar (SAR) data can be combined in an integrated multi-source framework to identify burned areas at the regional scale. The proposed approach is based on the use of fuzzy sets theory and a region-growing algorithm. Landsat TM and (C-band) ENVISAT Advanced Synthetic Aperture Radar (ASAR) images acquired for the year 2003 have been processed to extract burned area maps over Portugal. Pre-post fire SAR backscatter temporal difference has been integrated with optical spectral indices to the aim of reducing confusion between burned areas and low-albedo surfaces. The output fuzzy score maps have been compared with reference fire perimeters provided by the Fire Atlas of Portugal. Results show that commission and omission errors in the output burned area maps are a function of the threshold applied to the fuzzy score maps; between the two extremes of the greatest producer’s accuracy (omission error < 10%) and user’s accuracy (commission error < 5%), an intermediate threshold value provides errors of about 20% over the study area. The integration of SAR backscatter allowed reducing local commission errors from 65.4% (using optical data, only) to 11.4%, showing to significantly mitigate local errors due to the presence of cloud shadows and wetland areas. Overall, the proposed method is flexible and open to further developments; also in the perspective of the European Space Agency (ESA) Sentinel missions operationally providing SAR and optical datasets.

The Space-Borne SBAS-DInSAR Technique as a Supporting Tool for Sustainable Urban Policies: The Case of Istanbul Megacity, Turkey

In today’s urbanizing world, home of 28 megacities, there is a growing need for tools to assess urban policies and support the design and implementation of effective development strategies. Unsustainable practices of urbanization bring major implications for land and environment, and cause a dramatic increase of urban vulnerability to natural hazards. In Istanbul megacity, disaster risk reduction represents a challenging issue for urban managers. In this paper, we show the relevance of the space-borne Differential SAR Interferometry (DInSAR) technique as a tool for supporting risk management, and thus contributing to achieve the urban sustainability. To this aim, we use a dataset of high resolution SAR images collected by the TerraSAR-X satellite that have been processed through the advanced (multi-temporal) Small BAseline Subset (SBAS)—DInSAR technique, thus producing spatially-dense deformation velocity maps and associated time-series. Results allow to depict an up-to-date picture of surface deformations occurring in Istanbul, and thus to identify urban areas subject to potential risk. The joint analysis of remotely sensed measurements and ancillary data (geological and urban development information) provides an opportunity for city planners and land professionals to discuss on the mutual relationship between urban development policies and natural/man-made hazards.

A Minimum Acceleration Approach for the Retrieval of Multiplatform InSAR Deformation Time Series

We present in this paper a technique for the generation of 3-D (2-D) displacement time series of the earths surface, based on the combination of multiplatform SAR data. The algorithm assumes the availability of two (or more) archives of SAR images acquired from complementary (i.e., ascending/descending) tracks over the same area on the ground. SAR data are preprocessed through one of the currently available multitemporal differential interferometry synthetic aperture radar (DInSAR) toolboxes in order to recover, in correspondence to a set of very coherent points, the line-of-sight (LOS) displacement time series. The latter are then geocoded to a common grid and jointly inverted (pixel-by-pixel) to estimate the (unknown) time series of the 3-D (East-West, North-South, Up-Down) displacement components. To this aim, an underdetermined system of linear equations has to be solved. Previous works have proposed to solve similar ill-posed problems by applying the (truncated) singular-value-decomposition method and/or by regularizing the germane system of linear equations by adding further constraints, which impose conditions on the minimum-norm velocity of the solution. On the contrary, in this study, we adopt a different strategy, which is based on imposing that the 3-D deformation time series have minimum acceleration. The developed combination technique is a postprocessing tool that can be easily implemented. Indeed, it does not require the simultaneous processing of very large sequences of DInSAR interferograms. As a matter of fact, the retrieval of preliminary LOS-projected DInSAR time series can be independently carried out by using one (or more) of the currently available multitemporal DInSAR toolboxes, with no restrictions at all on the class to which they belong (small-baseline- and/or permanent-scatterers-oriented). Experiments carried out on simulated and real data prove the validity of the proposed combination algorithm in retrieving 2-D (East-West, Up-Down) surface displacement time series with subcentimeter accuracy, and the North-South components with an accuracy of some centimeters.

Effect of the Vegetation Fire on Backscattering: An Investigation Based on Sentinel-1 Observations

This paper aims at investigating the potential of Sentinel-1 C-band synthetic aperture radar (SAR) observations for detecting fire scars in vegetated areas at regional scale. A comprehensive analysis of the backscattering coefficients is carried out. The experimental analysis is conducted by analyzing the scenario of the Sardinia Island, which is one of the Italian regions most affected by fire events over the summer season. The detection capability of fire scars in such an environment is demonstrated by exploiting information extracted from dual-polarized SAR data. Our results reveal a significant decrease of the VH response over the fire-disturbed forests, thus, highlighting the effectiveness of such cross-polarized observations. In order to prove the validity of the proposed approach for the detection of fire scars in the vegetation layer, the results of the conducted experiments have been suitably compared with burned areas identified by using an existing fuzzy-based algorithm, which has been applied to multispectral Landsat-8 operational land imager data. This investigation opens the way to systematic methods for monitoring fire scars in heterogeneous environments, and in particular in fire-prone Mediterranean ecosystems.

Evaluation of the SBAS InSAR Service of the European Space Agency’s Geohazard Exploitation Platform (GEP)

The analysis of remote sensing data to assess geohazards is being improved by web-based platforms and collaborative projects, such as the Geohazard Exploitation Platform (GEP) of the European Space Agency (ESA). This paper presents the evaluation of a surface velocity map that is generated by this platform. The map was produced through an unsupervised Multi-temporal InSAR (MTI) analysis applying the Parallel-SBAS (P-SBAS) algorithm to 25 ENVISAT satellite images from the South of Spain that were acquired between 2003 and 2008. This analysis was carried out using a service implemented in the GEP called “SBAS InSAR”. Thanks to the map that was generated by the SBAS InSAR service, we identified processes not documented so far; provided new monitoring data in places affected by known ground instabilities; defined the area affected by these instabilities; and, studied a case where GEP could have been able to help in the forecast of a slope movement reactivation. This amply demonstrates the reliability and usefulness of the GEP, and shows how web-based platforms may enhance the capacity to identify, monitor, and assess hazards that are associated to geological processes.

DInSAR-Based Detection of Land Subsidence and Correlation with Groundwater Depletion in Konya Plain, Turkey

In areas where groundwater overexploitation occurs, land subsidence triggered by aquifer compaction is observed, resulting in high socio-economic impacts for the affected communities. In this paper, we focus on the Konya region, one of the leading economic centers in the agricultural and industrial sectors in Turkey. We present a multi-source data approach aimed at investigating the complex and fragile environment of this area which is heavily affected by groundwater drawdown and ground subsidence. In particular, in order to analyze the spatial and temporal pattern of the subsidence process we use the Small BAseline Subset DInSAR technique to process two datasets of ENVISAT SAR images spanning the 2002–2010 period. The produced ground deformation maps and associated time-series allow us to detect a wide land subsidence extending for about 1200 km2 and measure vertical displacements reaching up to 10 cm in the observed time interval. DInSAR results, complemented with climatic, stratigraphic and piezometric data as well as with land-cover changes information, allow us to give more insights on the impact of climate changes and human activities on groundwater resources depletion and land subsidence.

Preliminary analysis of a correlation between ground deformations and rainfall: the Ivancich landslide, central Italy

We exploited Differential Synthetic Aperture Radar Interferometry (DInSAR) to investigate the geographical and the temporal pattern of ground deformations in the Ivancich landslide area, Assisi, Italy, in the 18.4-year period April 1992 - September 2010. We used SAR data obtained by the European Remote Sensing (ERS-1/2) satellites in the period April 1992 - July 2007, and SAR data captured by the ASAR sensor on board the Envisat satellite in the period October 2003 - September 2010. We used the Small Baseline Subset (SBAS) technique to process the SAR data, obtaining full resolution measurements for multiple radar targets inside and outside the landslide area, and the history of deformation of the individual targets. The geographical pattern of the ground deformation was found consistent with independent topographic information. The deformation time series of the individual targets were compared to the rainfall history in the area. Results revealed the lack of an immediate effect of rainfall on the ground deformation, and confirmed the existence of a complex temporal interaction between the rainfall and the ground deformation histories in the landslide area. Availability of very long, spatially distributed time series of surface deformation has provided an unprecedented opportunity to investigate the history of the active landslide area.

Remote sensing of burned area: A fuzzy-based framework for joint processing of optical and microwave data

The application of an integrated monitoring tool to assess and understand the effects of annually occurring forest fires is presented, with special emphasis to Mediterranean and Temperate Continental zones of Europe. The distinctive features of the information conveyed by optical and microwave remote sensing data have been firstly investigated, and pertinent information have been subsequently combined to identify burned areas at the regional scale. We therefore propose a fuzzy-based multisource framework for burned area mapping, in order to overcome the limitations inherent to the use of only optical data (which can be severely affected by cloud cover or include low albedo surface targets). The relevant experimental validation has been carried out on an extensive area, thus quantitatively demonstrating how our approach successes in identifying areas affected by fires. Furthermore, the proposed methodological framework can also be profitably applied to Sentinel (optical and SAR) data.