Bert Kampes

Ambiguity resolution for permanent scatterer interferometry

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.

Remote sensing observation of mining induced subsidence by means of differential SAR-interferometry

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.

Salt diapir movements using SAR interferometry in the Lisan Peninsula, Dead Sea Rift

A several kilometres thick sequence of mostly marine salt with inter-bedded gypsum, shale and dolomite rock of Pliocene to Pleistocene age build several salt diapirs in the Dead Sea area. The Lisan Peninsula salt diapir is elongated in the N-S direction, and includes several sub-domes and a structural depression. Differential interferograms were generated for several time intervals of seven to ninety three months between 1992 and 1999 and show a large diversity of uplift and subsidence features in the peninsula. The uplift rate, which has been measured, is in correspondence to the geological rate evaluated by other geological researches. The subsidence, mainly in the south dome and the cape are much more significant. Inversion deformation in the cape between the year 1995-1996 suggested to be linked to the 22 November 1995 Nuweiba earthquake. This paper suggested a tectonic mechanism connecting the salt deformation in the Lisan Peninsula with the activity of Boqeq fault.

Physical analysis of atmospheric delay signal observed in stacked radar interferometric data

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.

Analysis of geosar dual-band InSAR data for peruvian forest

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.

Strategies for non-linear deformation estimation from interferometric stacks

A testing procedure is presented to estimate topography and deformation parameters from an interferometric stack (a number of reference phase corrected interferograms w.r.t. the same master image). A subset of pixels exhibit coherent phase in time, and a time series of phase differences between pairs of these pixels allows to set up a system of equations. A null hypothesis of zero deformation can be tested against alternative hypotheses, specifying linear and non-linear deformation. The covariance matrix of the phase differences accounts for phase noise, atmospheric effects, and orbit inaccuracies.

On the treatment of radar interferometry in terms of geodetic adjustment and testing theory

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.