Temporal and geometrical decorrelation often prevents SAR interferometry from being an operational tool for surface deformation monitoring and topographic profile reconstruction. Moreover, atmospheric disturbances can strongly compromise the accuracy of the results. The authors present a complete procedure for the identification and exploitation of stable natural reflectors or permanent scatterers (PSs) starting from long temporal series of interferometric SAR images. When, as it often happens, the dimension of the PS is smaller than the resolution cell, the coherence is good even for interferograms with baselines larger than the decorrelation one, and all the available images of the ESA ERS data set can be successfully exploited. On these pixels, submeter DEM accuracy and millimetric terrain motion detection can be achieved, since atmospheric phase screen (APS) contributions can be estimated and removed. Examples are then shown of small motion measurements, DEM refinement, and APS estimation and removal in the case of a sliding area in Ancona, Italy. ERS data have been used.

Permanent scatterers in SAR interferometry

We present a new differential synthetic aperture radar (SAR) interferometry algorithm for monitoring the temporal evolution of surface deformations. The presented technique is based on an appropriate combination of differential interferograms produced by data pairs characterized by a small orbital separation (baseline) in order to limit the spatial decorrelation phenomena. The application of the singular value decomposition method allows us to easily "link" independent SAR acquisition datasets, separated by large baselines, thus increasing the observation temporal sampling rate. The availability of both spatial and temporal information in the processed data is used to identify and filter out atmospheric phase artifacts. We present results obtained on the data acquired from 1992 to 2000 by the European Remote Sensing satellites and relative to the Campi Flegrei caldera and to the city of Naples, Italy, that demonstrate the capability of the proposed approach to follow the dynamics of the detected deformations.

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A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms

Synthetic aperture radar interferometry is an imaging technique for measuring the topography of a surface, its changes over time, and other changes in the detailed characteristic of the surface. By exploiting the phase of the coherent radar signal, interferometry has transformed radar remote sensing from a largely interpretive science to a quantitative tool, with applications in cartography, geodesy, land cover characterization, and natural hazards. This paper reviews the techniques of interferometry, systems and limitations, and applications in a rapidly growing area of science and engineering.

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Synthetic aperture radar interferometry

Geophysical applications of radar interferometry to measure changes in the Earth's surface have exploded in the early 1990s. This new geodetic technique calculates the interference pattern caused by the difference in phase between two images acquired by a spaceborne synthetic aperture radar at two distinct times. The resulting interferogram is a contour map of the change in distance between the ground and the radar instrument. These maps provide an unsurpassed spatial sampling density (∼100 pixels km−2), a competitive precision (∼1 cm), and a useful observation cadence (1 pass month−1). They record movements in the crust, perturbations in the atmosphere, dielectric modifications in the soil, and relief in the topography. They are also sensitive to technical effects, such as relative variations in the radar's trajectory or variations in its frequency standard. We describe how all these phenomena contribute to an interferogram. Then a practical summary explains the techniques for calculating and manipulating interferograms from various radar instruments, including the four satellites currently in orbit: ERS-1, ERS-2, JERS-1, and RADARSAT. The next chapter suggests some guidelines for interpreting an interferogram as a geophysical measurement: respecting the limits of the technique, assessing its uncertainty, recognizing artifacts, and discriminating different types of signal. We then review the geophysical applications published to date, most of which study deformation related to earthquakes, volcanoes, and glaciers using ERS-1 data. We also show examples of monitoring natural hazards and environmental alterations related to landslides, subsidence, and agriculture. In addition, we consider subtler geophysical signals such as postseismic relaxation, tidal loading of coastal areas, and interseismic strain accumulation. We conclude with our perspectives on the future of radar interferometry. The objective of the review is for the reader to develop the physical understanding necessary to calculate an interferogram and the geophysical intuition necessary to interpret it.

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Radar interferometry and its application to changes in the Earth's surface

GEODETIC data, obtained by ground- or space-based techniques, can be used to infer the distribution of slip on a fault that has ruptured in an earthquake. Although most geodetic techniques require a surveyed network to be in place before the earthquake1–3, satellite images, when collected at regular intervals, can capture co-seismic displacements without advance knowledge of the earthquake's location. Synthetic aperture radar (SAR) interferometry, first introduced4 in 1974 for topographic mapping5–8 can also be used to detect changes in the ground surface, by removing the signal from the topography9,10. Here we use SAR interferometry to capture the movements produced by the 1992 earthquake in Landers, California11. We construct an interferogram by combining topographic information with SAR images obtained by the ERS-1 satellite before and after the earthquake. The observed changes in range from the ground surface to the satellite agree well with the slip measured in the field, with the displacements measured by surveying, and with the results of an elastic dislocation model. As a geodetic tool, the SAR interferogram provides a denser spatial sampling (100 m per pixel) than surveying methods1–3 and a better precision (∼3 cm) than previous space imaging techniques12,13.

The displacement field of the Landers earthquake mapped by radar interferometry

Discrete and temporarily stable natural reflectors or permanent scatterers (PS) can be identified from long temporal series of interferometric SAR images even with baselines larger than the so-called critical baseline. This subset of image pixels can be exploited successfully for high accuracy differential measurements. The authors discuss the use of PS in urban areas, like Pomona, CA, showing subsidence and absidence effects. A new approach to the estimation of the atmospheric phase contributions, and the local displacement field is proposed based on simple statistical assumptions. New solutions are presented in order to cope with nonlinear motion of the targets.

/pdf/nonlinear-subsidence-rate-estimation-using-permanent-4ppv4mgnmr.pdf

Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry

Permanent Scatterer SAR Interferometry (PSInSAR) aims to identify coherent radar targets exhibiting high phase stability over the entire observation time period. These targets often correspond to point-wise, man-made objects widely available over a city, but less present in non-urban areas. To overcome the limits of PSInSAR, analysis of interferometric data-stacks should aim at extracting geophysical parameters not only from point-wise deterministic objects (i.e., PS), but also from distributed scatterers (DS). Rather than developing hybrid processing chains where two or more algorithms are applied to the same data-stack, and results are then combined, in this paper we introduce a new approach, SqueeSAR, to jointly process PS and DS, taking into account their different statistical behavior. As it will be shown, PS and DS can be jointly processed without the need for significant changes to the traditional PSInSAR processing chain and without the need to unwrap hundreds of interferograms, provided that the coherence matrix associated with each DS is properly “squeezed” to provide a vector of optimum (wrapped) phase values. Results on real SAR data, acquired over an Alpine area, challenging for any InSAR analysis, confirm the effectiveness of this new approach.

A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR

Differential SAR interferometry measurements provide a unique tool for low-cost, large-coverage surface deformations monitoring. Limitations are essentially due to temporal decorrelation and atmospheric inhomogeneities. Though temporal decorrelation and atmospheric disturbances strongly affect interferogram quality, reliable deformation measurements can be obtained in a multi-image framework on a small subset of image pixels, corresponding to stable areas. These points, hereafter called Permanent Scatterers, can be used as a `natural GPS network' to monitor terrain motion, analyzing the phase history of each one. In this paper, results obtained using 45 ERS SAR images gathered over the Italian town of Camaiore (within a time span of more than 6 years and a range of normal baseline of more than 2000 m) are presented. The area is of high geophysical interest because it is known to be unstable. A subterranean cavity collapsed in October 1995 causing the ruin of several houses in that location. Time series analysis of the phase values showed the presence of precursors three months before the collapse.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

SAR surveys from separate passes show relative shifts of the ground wavenumber spectra that depend on the local slope and the off-nadir angle. The authors discuss the exploitation of this spectral shift for different applications: 1) generation of "low noise" interferograms benefiting phase unwrapping, 2) generation of quick-look interferograms, 3) decorrelation reduction by means of tunable SAR systems (TINSAR), 4) range resolution enhancement, and 5) the combination of SAR data gathered by different platforms (airborne and satellite) for a "long-time coherence" study. >

Claudio Prati

Papers

Permanent scatterers in SAR interferometry

Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry

A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR

Permanent scatterers in SAR interferometry

The wavenumber shift in SAR interferometry