Bruno Crippa

The Thermal Expansion Component of Persistent Scatterer Interferometry Observations

This letter focuses on the thermal expansion component of persistent scatterer (PS) interferometry (PSI), which is a result of temperature differences in the imaged area between synthetic aperture radar (SAR) acquisitions. This letter is based on very high resolution X-band StripMap SAR data captured by the TerraSAR-X spaceborne sensor. The X-band SAR interferometric phases are highly influenced by the thermal dilation of the imaged objects. This phenomenon can have a strong impact on the PSI products, particularly on the deformation velocity maps, if not properly handled during the PSI analysis. In this letter, we propose a strategy to deal with the thermal dilation phase component, which involves further developing the standard two-parameter PSI model (deformation velocity and residual topographic error) with a third unknown parameter called the thermal dilation parameter, which is estimated for each PS. The map obtained from plotting this parameter for all PSs of a given area is hereafter called thermal map. This letter describes the proposed model and outlines the issue of parameter estimability. In addition, the potential of exploiting the thermal maps is analyzed by illustrating two examples of the Barcelona (Spain) metropolitan area. Thermal maps provide two types of information: The first one is the coefficient of thermal expansion of the observed objects, while the second one, which is related to the pattern of the thermal dilation parameter, gives information about the static structure of these objects. Two important aspects that influence the exploitation of thermal maps are discussed in the last section of this letter: the line-of-sight nature of the derived estimates and the achievable precision in the estimation of the coefficient of thermal expansion.

Spaceborne Differential SAR Interferometry: Data Analysis Tools for Deformation Measurement

This paper is focused on spaceborne Differential Interferometric SAR (DInSAR) for land deformation measurement and monitoring. In the last two decades several DInSAR data analysis procedures have been proposed. The objective of this paper is to describe the DInSAR data processing and analysis tools developed at the Institute of Geomatics in almost ten years of research activities. Four main DInSAR analysis procedures are described, which range from the standard DInSAR analysis based on a single interferogram to more advanced Persistent Scatterer Interferometry (PSI) approaches. These different procedures guarantee a sufficient flexibility in DInSAR data processing. In order to provide a technical insight into these analysis procedures, a whole section discusses their main data processing and analysis steps, especially those needed in PSI analyses. A specific section is devoted to the core of our PSI analysis tools: the so-called 2+1D phase unwrapping procedure, which couples a 2D phase unwrapping, performed interferogram-wise, with a kind of 1D phase unwrapping along time, performed pixel-wise. In the last part of the paper, some examples of DInSAR results are discussed, which were derived by standard DInSAR or PSI analyses. Most of these results were derived from X-band SAR data coming from the TerraSAR-X and CosmoSkyMed sensors.

An Approach to Persistent Scatterer Interferometry

This paper describes a new approach to Persistent Scatterer Interferometry (PSI) data processing and analysis, which is implemented in the PSI chain of the Geomatics (PSIG) Division of CTTC. This approach includes three main processing blocks. In the first one, a set of correctly unwrapped and temporally ordered phases are derived, which are computed on Persistent Scatterers (PSs) that cover homogeneously the area of interest. The key element of this block is given by the so-called Cousin PSs (CPSs), which are PSs characterized by a moderate spatial phase variation that ensures a correct phase unwrapping. This block makes use of flexible tools to check the consistency of phase unwrapping and guarantee a uniform CPS coverage. In the second block, the above phases are used to estimate the atmospheric phase screen. The third block is used to derive the PS deformation velocity and time series. Its key tool is a new 2+1D phase unwrapping algorithm. The procedure offers different tools to globally control the quality of the processing steps. The PSIG procedure has been successfully tested over urban, rural and vegetated areas using X-band PSI data. Its performance is illustrated using 28 TerraSAR-X StripMap images over the metropolitan area of Barcelona.

Exploitation of high‐density DInSAR data points of the Umbria‐Marche (Italy) 1997 seismic sequence for fault characteristics

[1] High spatial resolution DInSAR data for the Umbria Marche 1997 seismic sequence are exploited by relaxing constraints derived from datasets of different nature, such as seismologically derived fault dimensions. DInSAR data are thus inverted for a realistic slip distribution over the faults, in terms of depth distribution and roughness, which allows us to relocate the main faults and to minimize the misfit between the vertical displacement pattern derived from DInSAR and model predictions. Our analysis reveals that slip affected not only the shallowest part of the fault system but also its deepest part, rupturing the whole seismogenic layer of the crust down to 10 km, reaching slip values up to 30 cm at the base of the seismogenic layer. Misfit is reduced by a factor of two with respect to previous analyses based on a smaller number of digitized fringe points.

The SISMA prototype system: integrating Geophysical Modeling and Earth Observation for time dependent seismic hazard assessment

An innovative approach to seismic hazard assessment is illustrated that, based on the available knowledge of the physical properties of the Earth structure and of seismic sources, on geodetic observations, as well as on the geophysical forward modeling, allows for a time-dependent definition of the seismic input. According to the proposed approach, a fully formalized system integrating Earth Observation data and new advanced methods in seismological and geophysical data analysis is currently under development in the framework of the Pilot Project SISMA, funded by the Italian Space Agency. The synergic use of geodetic Earth Observation data (EO) and Geophysical Forward Modeling deformation maps at the national scale complements the space- and time-dependent information provided by real-time monitoring of seismic flow (performed by means of the earthquake prediction algorithms CN and M8S) and permits the identification and routine updating of alerted areas. At the local spatial scale (tens of km) of the seismogenic nodes identified by pattern-recognition analysis, both GNSS (Global Navigation Satellite System) and SAR (Synthetic Aperture Radar) techniques, coupled with expressly developed models for interseismic phase, allow us to retrieve the deformation style and stress evolution within the seismogenic areas. The displacement fields obtained from EO data provide the input for the geophysical modeling, which eventually permits to indicate whether a specific fault is in a “critical state.” The scenarios of expected ground motion (shakemaps) associated with the alerted areas are then defined by means of full waveforms modeling, based on the possibility to compute synthetic seismograms by the modal summation technique (neo-deterministic hazard assessment). In this way, a set of deterministic scenarios of ground motion, which refer to the time interval when a strong event is likely to occur within the alerted area, can be defined both at national and at local scale. The considered integrated approach opens new routes in understanding the dynamics of fault zones as well as in modeling the expected ground motion. The SISMA system, in fact, provides tools for establishing warning criteria based on deterministic and rigorous forward geophysical models and hence allows for a well-controlled real-time prospective testing and validation of the proposed methodology over the Italian territory. The proposed approach complements the traditional probabilistic approach for seismic hazard estimates, since it supplies routinely updated information useful in assigning priorities for timely mitigation actions and hence it is particularly relevant to Civil Defense purposes.

A new product from persistent scatterer interferometry: The thermal dilation maps

Persistent Scatterer Interferometry (PSI) is a remote sensing technique to measure and monitor land deformation from a stack of interferometric SAR images. Its main products are the deformation maps (maps of the average displacement rates), the deformation time series and the maps of the so-called residual topographic errors. In this paper, we describe a new product derived from X-band PSI: the thermal deformation maps. This paper briefly describes the thermal component of the PSI phase observations and outlines the approach to estimate the thermal maps. The last part of the paper discusses three examples of thermal maps derived from a stack of 28 StripMap TerraSAR-X images that cover the metropolitan area of Barcelona (Spain).

Coupling geophysical modelling and geodesy to unravel the physics of active faults

The major requirements of seismic hazard assessment must address mainly the information about the expected location, time and magnitude of the impending strong earthquakes, as well as the scenarios ground motion associated with the possible future seismic events. While the quick notification of seismic events, appears nowadays pretty well established, thanks to the development of regional and local seismic networks, in terms of prevention more and more importance is devoted to studies of the inter- and pre- seismic earthquake cycle. To improve the intra seismic and pre-seismic information, which may lead to an effective mitigation of seismic risk, we are proposing an innovative approach, that combines Earth Observation data (GPS and SAR) and new advanced approaches in seismological and geophysical data analysis. The employed EO data are the observations acquired by means of SAR sensors, treated by Differential Interferometric techniques, the data observation acquired by permanent GPS stations or ¿ad-hoc¿ campaigns of the observations done over earthquake prone area. The aim is to combine the geophysical modelling of the faults with the surface displacement measured with the two mentioned techniques. In particular, application of the DInSAR techniques, using a stacking of interferograms, makes it possible, under the classical interferometric constraints (coherence, baseline, etc.), to retrieve a vertical displacements map, referred to a temporal interval, over areas where seismic fault system are localized. The displacements fields coming from GPS/DInSAR and other additional information, constitute the input for the geophysical model which shall indicate whether the fault is in a ¿critical situation¿.

Quantitative subsidence monitoring using SAR interferometry

The paper describes the main characteristics of three procedures to perform subsidence monitoring using SAR interferometry, which are suitable to support quantitative applications, like those related to risk assessment and public safety. The first procedure can be effective even with a single interferogram, while the other ones are suitable to the configurations based on multiple interferograms.

Sentinel-1 Data Analysis for Landslide Detection and Mapping: First Experiences in Italy and Spain

Open image in new window The differential interferometric SAR (DInSAR) technique is a powerful tool to detect and monitor ground deformation. In this paper we address an important DInSAR application, which is the detection and mapping of landslides. The potential of DInSAR to detect and monitor landslides has been extensively documented in the literature, mainly using the C-band data from the European Remote Sensing (ERS-1 and -2), Envisat and Radarsat missions. A significant improvement in landslide monitoring is expected by the SAR data of the two satellites Sentinel-1A and -1B of the European Space Agency. This paper describes the authors’ first experience using Sentinel-1 for landslide monitoring. The paper describes the data processing and analysis strategy, and then illustrates some deformation measurement results obtained over Italy and Spain.

SAR interferometry for deformation control

A quantitative control of deformations using the differential interferometric SAR (DInSAR) technique may be achieved when multiple observations and suitable modelling and analysis tools are employed. The paper begins with a description of the main characteristics of the DInSAR data. Then, it discusses a new modelling and filtering strategy, which takes advantage of the specific properties of the DInSAR observations. The core of the procedure is the least squares collocation filtering and prediction, which exploits the correlation properties of the DInSAR data. The proposed procedure was tested on simulated DInSAR data that reproduce the characteristics of a small scale subsidence, and that include the main components of the interferometric data: the atmospheric contribution, the phase noise component, and the outliers due to the unwrapping related errors.