Luca Pietranera

Use of differential SAR interferometry in monitoring and modelling large slope instability at Maratea (Basilicata, Italy)

Abstract Differential Synthetic Aperture Radar (SAR) interferometry (DiffSAR) allows, in principle, to measure very small movements of the ground and to cover in continuity large areas, so that it can be considered as a potentially ideal tool to investigate landslides and other slope instability. In this paper, we explore the use of this technique to improve our knowledge of the slope instability of a well-investigated area (the Maratea Valley), affected by continuous slow movements, producing an impressive “Sackung”-type phenomenon, which poses several unanswered questions. In particular, by using this technique, we analyse the time evolution of ground movements from 1997 to 2000. The slope movements during this same time interval have also been monitored in the past by using other techniques, such as electronic distance-meter (EDM) and GPS measurements: GPS and DiffSAR results are here compared. In our implementation of the DiffSAR technique, the problem of decorrelation noise is faced by using a phase unwrapping approach that allows to process sparse data, and the impact of atmospheric artefacts is reduced by performing a temporal analysis of the deformations observed in successive interferograms. In this study, we also show that it is possible to perform a temporal analysis of continuous slow landslide movements by using a limited number of ERS SAR data sets and low-precision topographic information. All the acquired data (EDM, GPS and DiffSAR) are consistent and allow a kinematic model of instability within the investigated time interval to be proposed. A map of slopes subject to different velocities of vertical displacements was delineated, modifying previous knowledge. Within the valley, progressive and almost linear displacements over time were confirmed.

SAR and InSAR for Flood Monitoring: Examples With COSMO-SkyMed Data

We apply high-resolution, X-band, stripmap COSMO-SkyMed data to the monitoring of flood events in the Basilicata region (Southern Italy), where multitemporal datasets are available with short spatial and temporal baselines, allowing interferometric (InSAR) processing. We show how the use of the interferometric coherence information can help to detect more precisely the areas affected by the flood, reducing false alarms and missed identifications which affect algorithms based on SAR intensity alone. The effectiveness of using the additional InSAR information layer is illustrated by RGB composites of various combinations of intensity and coherence data. Analysis of multitemporal SAR intensity and coherence trends reveals complex behavior of various field types, which we interpret through a Bayesian inference approach, based on a manual identification of representative scattering and coherence signatures of selected homogeneous fields. The approach allows to integrate external, ancillary information to derive a posteriori probabilistic maps of flood inundation accounting for different scattering responses to the presence of water. First results of this semiautomated methodology, using simple assumptions for the SAR signatures and a priori information based on the distance from river courses, show encouraging results, and open a path to improvement through use of more complex hydrologic and topo-hydrographic information.

Monitoring terrain movements by means of sparse SAR differential interferometric measurements

Synthetic aperture radar differential interferometry is a powerful technique that allows, in principle, the measurement of very small movements of the terrain over time. Unfortunately, SAR differential interferograms are often rather noisy. A recently proposed phase unwrapping approach allows sparse data to be processed, and therefore extraction of the available information from noisy data sets. The authors test the potential of this method on several SAR differential interferometric data sets. In particular, the subsidence phenomena happening in Bologna (Italy) and in the surrounding area from 1993 to 1999 are analyzed. Unwrapped phases corresponding to different pairs are finally combined to perform a full space-time analysis of the considered phenomena.

A three-dimensional phase unwrapping algorithm for processing of multitemporal SAR interferometric measurements

Phase unwrapping is the problem of reconstructing a function on a grid given its values modulo 2/spl pi/. This is a key problem in SAR interferometry and in other fields. The typical availability of multiple 2D SAR interferograms of the same scene suggest the possibility of considering the data as samples of a function in a 3D space-time. This helps better reconstructing the right solution, in the same way as 2D phase unwrapping provides more reliable solutions than the 1D (quite trivial) algorithm. However, computational needs result increased in the 3D case. In this work we describe the proposed algorithm for 3D phase unwrapping, and show the results obtained on simulated and real SAR images.

Analysis and correction of artifacts on differential SAR interferometry for the study of subsidence phenomena

This paper deals with the analysis and correction of artifacts on differential synthetic aperture radar (SAR) interferometry. Particularly, we concentrate on those artifacts arising from the use in interferometric processing of low accuracy acquisition geometry data. To remove these artifacts, we propose a new algorithm able to estimate the acquisition geometry parameters with high accuracy directly from the SAR data. The application of the proposed technique to the study of the subsidence phenomena in Bologna (Italy) and the surrounding area is also presented to validate the new algorithm.

Temporal analysis of terrain subsidence by means of sparse SAR differential interferometric measurements

Synthetic aperture radar (SAR) differential interferometry allows, in principle, to measure very small movements of the terrain. Main limitations of this technique include decorrelation noise and atmospheric artifacts that can affect SAR differential interferograms. In this paper we show that the problem of decorrelation noise can be efficiently faced by using a new phase unwrapping approach that allows to process sparse data, and that the impact of atmospheric artifacts can be minimized by performing a temporal analysis of the deformations observed in successive SAR differential interferograms. Also, in this study we show that it is possible to perform a temporal analysis of slow terrain movements by using a rather limited number of ERS SAR data set and low precision topographic information. As an application of the proposed technique, the subsidence phenomena occurring in Bologna (Italy) and in the surrounding area from 1992 to 1999 are analyzed.

SAR and InSAR for flood monitoring: Examples with COSMO/SkyMed data

We apply high-resolution, X-band, stripmap COSMO/SkyMed data to the monitoring of a flood event in Southern Basilicata region (Italy), where a multi-temporal dataset is available, allowing interferometric processing. We show how the use of the interferometric phase information can actually help to detect precisely the areas affected by the flood, using e.g. RGB composites of various information layers derived from the data. We also present results of unsupervised clustering of the multi-temporal data, which allow to shed some light on the physical interpretation of some of the identified clusters.

Sea surface transport derived by frequent revisit time series of COSMO SkyMed SAR data

The surface transport of ‘SAR detectable’ features on sea is accurately estimated by couples of overlapping COSMO SkyMed ScanSAR images acquired with a very short time lag (below the hour). Tests performed with the two satellites constellation during 2008 (4 operative by 2010) provided pairs of overlapping images with a time shift of 48 minutes and with a repeat time from 12 to 24h. The short time lag acquisition has two advantages: the first is that the pair of overlapping images is a sort of time derivative from which an accurate estimate of the surface transport can be extracted, the second is that the deformation of the ‘tracked features’ in the short time interval is minimal and a large number of objects can be tracked, even with the only automated processing. The sea surface transport is a crucial data in case of marine emergencies and the accurate estimate greatly improves the surveillance and the forecasting capability. Overlapping and short time lagged SAR imagery provide surface transport data of detectable objects with all-weather conditions.

Differential SAR interferometry for the study of slope instability at Maratea, Italy

In this paper we explore the use of differential synthetic aperture radar interferometry to improve our knowledge of the slope instability of a well investigated area (the Maratea Valley) affected by continuous slow movements. In particular, by using this technique we analyse the time evolution of terrain movements from 1997 to 2000, a time interval already explored using distancemeter (EDM) and GPS measurements. Results obtained by means of different techniques have been compared, and all the acquired data turn out to be consistent.

COSMO-SkyMed mission: risk management applications over China, Myanmar and Haiti conducted during 2008

Between 2007 and 2008, Agenzia Spaziale Italiana (ASI) and Ministero della Difesa (Italian Ministry of Defence) launched three out of the four X-band SAR (synthetic aperture radar) satellites of the Constellation of Small Satellites for Mediterranean Basin Observation (COSMO-SkyMed) dual-use (civilian and defence) mission, dedicated to Earth observation. The results received from the utilization of the two operative satellites of the constellation reveal the significant achievement of the X-band SAR sensor and the importance of a fast response time in risk management applications. This article presents the qualitative analyses and results related to a set of risk management applications of the year 2008 by ASI and e-GEOS pertaining to China, Myanmar and Haiti.