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P-band interferometric synthetic aperture radar (InSAR) data at 5 m resolution from Kahiltna Glacier, the largest glacier in the Alaska Range, Alaska, USA, show pronounced spatial variation in penetration depth, δP. We obtained δP by differencing X- and P-band digital elevation models. δP varied significantly over the glacier, but it was possible to distinguish representative zones. In the accumulation area, δP decreased with decreasing elevation from 18 ± 3 m in the percolation zone to 10 ± 4 m in the wet snow zone. In the central portion of the ablation area, a location free of debris and crevasses, we identified a zone of very high δP (34 ± 4 m) which decreased at lower elevations (23 ± 3 m in bare ice and 5-10m in debris-covered ice). We observe that the spatial configuration of δP is consistent with the expected thermal regime of each zone: δP is high in areas where cold firn/ice likely occurs (i.e. percolation zone and upper ablation area) and low in areas where temperate surface firn/ice likely exists (wet snow zone and lower ablation area). We suggest that the very high δP observed in the upper ablation area is due to the presence of a cold surface layer.

We present a modification to the adaptive Goldstein radar interferogram filter which improves the quality of interferometry products. The proposed approach makes the Goldstein filter parameter alpha dependent on coherence, such that incoherent areas are filtered more than coherent areas. This modification minimizes loss of signal while still reducing the level of noise.

At present there is no consensus as to which remote sensing technologies are appropriate for tropical forest biomass estimation. Cloud cover in the tropics and biomass saturation suggest that a combination of low-frequency SAR and interferometry (either PolInSAR or dual-band interferometric SAR - DBInSAR) could provide a solution.

We use a combination of Persistent Scatterer Interferometry (PSI) and GPS observations to study interseismic crustal deformation on the Gazikoy–Saros segment (Ganos fault) of the North Anatolian Fault (NAF) zone, northwestern Turkey. The data include 44 C-band radar images collected by the ERS1 and ERS2 satellites in descending orbits between 1992 and 2003 over the study area, and campaign GPS horizontal velocities from 7 stations. The resultant secular velocity field is inverted using a nonlinear minimization algorithm to estimate parameters of two interseismic deformation models: aseismic deep slip in a purely elastic earth model (elastic half-space rheology), and viscoelastic flow in an elastic–viscoelastic earth model (viscoelastic-coupling rheology). The following conclusions are drawn: (1) The fault locking depth is estimated in the range of ∼ 8–17 km (95% confidence interval) regardless of the rheological model. (2) The elastic half-space model implies an upper bound of 20–27 mm/yr for the slip rate on the Ganos fault. (3) Models incorporating viscoelastic rheology and seismic cycle effects suggest a lower slip rate of 18–24 mm/yr, which agrees more closely with geological estimates. However, these values are slightly sensitive to the assumed earthquake recurrence interval. (4) A bootstrap analysis of deformation data yields average crust-upper mantle viscosities of 1.3 × 10 19 –3.6 × 10 20 Pa s for the Ganos area.

[1] We present here a new InSAR persistent scatterer (PS) method for analyzing episodic crustal deformation in non-urban environments, with application to volcanic settings. Our method for identifying PS pixels in a series of interferograms is based primarily on phase characteristics and finds low-amplitude pixels with phase stability that are not identified by the existing amplitude-based algorithm. Our method also uses the spatial correlation of the phases rather than a well-defined phase history so that we can observe temporally-variable processes, e.g., volcanic deformation. The algorithm involves removing the residual topographic component of flattened interferogram phase for each PS, then unwrapping the PS phases both spatially and temporally. Our method finds scatterers with stable phase characteristics independent of amplitudes associated with man-made objects, and is applicable to areas where conventional InSAR fails due to complete decorrelation of the majority of scatterers, yet a few stable scatterers are present.

In the permanent scatterer technique of synthetic aperture radar interferometry, there is a need for an efficient and reliable nonlinear parameter inversion algorithm that includes estimation of the phase cycle ambiguities. Present techniques make use of a direct search of the solution space, treating the observations as deterministic and equally weighted, and which do not yield an exact solution. Moreover, they do not describe the quality of the estimated parameters. Here, we use the integer least squares estimator, which has the highest probability of correct integer estimation for problems with a multivariate normal distribution. With this estimator, the propagated variance-covariance matrix of the estimated parameters can be obtained. We have adapted the LAMBDA method, part of an integer least squares estimator developed for the ambiguity resolution of carrier phase observations in global positioning systems, to the problem of permanent scatterers. Key elements of the proposed method are the introduction of pseudo-observations to regularize the system of equations, decorrelation of the ambiguities for an efficient estimation, and the combination of a bootstrap estimator with an integer least squares search to obtain the final integer estimates. The performance of the proposed algorithm is demonstrated using simulated and real data.

This paper addresses the question of how to robustly estimate linear deformation at a large number of points from differential phase in an interferometric stack. The so-called "Permanent Scatterers technique" (Ferretti et al. 2001), uses a relatively large number of differential interferograms of the same area, co-registered at the same master SLC image. Linear deformation rates and DEM errors are estimated for pixels that have limited temporal decorrelation. This straightforward and generic setup has been used in a network approach that uses connections between nearby points to compute a velocity field for large areas.

We applied the differential SAR-interferometry to detect subsidence in the brown coal mining area of the Lower Rhine Embayment, Germany. The displacement is caused by groundwater withdrawal. For this approach, 40 ERS-1/-2 scenes covering a time interval of about 4 years were processed. In a first evaluation, a mean displacement rate of about 50 mm/yr was observed. This estimation agrees very well to the leveling measurements. In addition, we applied the Permanent Scatterer techniques in order to get a detailed understanding by pointwise information beside the spatial data.

An empirical power law based covariance function is presented to model atmospheric error signal in radar interferograms. Results for eight different independent interferograms are evaluated, and the mathematical modeling of radar interferometric data is discussed.

The aim of the GEDEX, which is being designed by an international team of scientists, is to explore the feasibility of Geodetic & Geodynamic applications of Space VLBI. In this paper, the outline of this experiment has been presented. A brief description of the Space VLBI technique has been provided, followed by a summary of the significant theoretical developments. Salient features of the VSOP mission. and an overview of the various aspects of GEDEX have been presented. The state of the art of software for Geodetic SVLBI has been outlined, and the different steps in software development for the GEDEX have been described in detail. Conclusions drawn from the work done so far, and recommendations for future work have been presented.

The main limiting factors for deformation mea- surements using repeat-pass satellite radar interferometry are temporal decorrelation of the scattering characteristics of the earth and atmospheric delay phase contributions to the interfer- ometric phase. Ferretti et al.(1) showed that using a multitude of radar acquisitions over the same site—a time series approach— reflections can be identified with a stable phase behavior in time, thus allowing deformation behavior to be estimated. The model of observation equations consists of m phase observations for a specific pixel and n unknown parameters describing surface deformation, elevation, and trend. Atmospheric delay is an important error source in these observations, but since it is temporally uncorrelated (while spatially correlated) it can be approximated per pixel per interferometric combination. This approximation requires a heuristic decision on which part of the temporal behavior of the interferometric phase is due to unmodelled deformation (e.g., non-linear deformation if the model estimates only linear deformation), and which part is due to uncorrelated atmospheric signal. Second, the residues attributed to atmosphere for all selected points within a single interferogram are expected to show spatial correlation, following a specific power law behavior (Hanssen, 2001). This results in a second decision on dividing atmospheric contribution and phase noise. Although the assumptions on which these two decisions are based are reasonable and results of previous studies show estimations of deformation and topography which are very likely, there is no independent means of control for the approach followed. In this paper, we will investigate the atmospheric signal estimated from a stack of 70 radar images acquired over Berlin, Germany. The estimated signal will be statistically parameterized and physically compared with meteorological data such as visual, infrared, and water vapor images from meteorological satellites and synoptic data. We will draw conclusions on the likelihood of the assumptions underlying the isolation of atmospheric signal, resulting in an increased reliability of the estimated parameters.