Urs Wegmüller

Interferometric point target analysis for deformation mapping

Interferometric Point Target Analysis (IPTA) is a method to exploit the temporal and spatial characteristics of interferometric signatures collected from point targets to accurately map surface deformation histories, terrain heights, and relative atmospheric path delays. In this contribution the IPTA concept is introduced, including the point selection criteria, the phase model and the iterative improvement of the model parameters. Intermediate and final results of an IPTA example using a stack of ERS-1 and ERS-2 data, confirm the validity of the concept and indicate a high accuracy of the resulting products.

Glacier motion estimation using SAR offset-tracking procedures

Two image-to-image patch offset techniques for estimating feature motion between satellite synthetic aperture radar (SAR) images are discussed. Intensity tracking, based on patch intensity cross-correlation optimization, and coherence tracking, based on patch coherence optimization, are used to estimate the movement of glacier surfaces between two SAR images in both slant-range and azimuth direction. The accuracy and application range of the two methods are examined in the case of the surge of Monacobreen in Northern Svalbard between 1992 and 1996. Offset-tracking procedures of SAR images are an alternative to differential SAR interferometry for the estimation of glacier motion when differential SAR interferometry is limited by loss of coherence, i.e. in the case of rapid and incoherent flow and of large acquisition time intervals between the two SAR images. In addition, an offset-tracking procedure in the azimuth direction may be combined with differential SAR interferometry in the slant-range direction in order to retrieve a two-dimensional displacement map when SAR data of only one orbit configuration are available.

Dielectric properties of fresh-water ice at microwave frequencies

So far, knowledge about the dielectric properties, especially the loss factor, of ice at microwave frequencies has been unsatisfactory. In this work the authors report on new measurements made over the frequency range from 2 to 100 GHz by a resonator method (2-10 GHz) and a radiometer method (10-100 GHz). Measurements were made with pure and with slightly saline (10 to 13 p.p.m.) ice. The results agree with the assumption of a single minimum of the dielectric loss at 2 to 4 GHz. For pure ice the data are a natural link between the measurements of Westphal made below 1 GHz and the far-infrared spectrum. The influence of small impurities on the dielectric loss is compared with the behaviour of sea ice, and it is found that the same linear relationship with salinity can be applied to both cases.

Retrieval of vegetation parameters with SAR interferometry

The potential of SAR interferometric techniques for the retrieval of vegetation parameters was investigated using ERS-1 data over agricultural and forested test sites. In a first experiment an interferometrically derived forest map was generated. The classification was based on the interferometric correlation and the backscatter intensities. The result was geocoded, using the interferometrically derived height map generated from the same ERS SAR data pair, and validated with a conventional digital forest map. Forest mapping accuracies of around 90% and better were achieved. In a second experiment, multitemporal data over an agricultural site were used to investigate the potential of repeat-pass interferometry to monitor farming activity, crop development, and soil moisture variations. The interferometric correlation was used as an indicator of dense vegetation and geometric change. It was possible, for example, to identify harvesting by the high correlation of the post-harvest bare or stubble field. Decreasing interferometric correlation was observed as a consequence of crop growth.

Rough bare soil reflectivity model

A semiempirical model for the reflectivity of rough bare soil is presented. One of the main objectives of this new model development was to derive a simple model with few model parameters and a wide applicability. A large number of ground-based measurements in the 1-100-GHz range at H and V-polarization and incidence angles between 20/spl deg/ and 70/spl deg/ were used for the model development.

An advanced system for the automatic classification of multitemporal SAR images

A novel system for the classification of multitemporal synthetic aperture radar (SAR) images is presented. It has been developed by integrating an analysis of the multitemporal SAR signal physics with a pattern recognition approach. The system is made up of a feature-extraction module and a neural-network classifier, as well as a set of standard preprocessing procedures. The feature-extraction module derives a set of features from a series of multitemporal SAR images. These features are based on the concepts of long-term coherence and backscattering temporal variability and have been defined according to an analysis of the multitemporal SAR signal behavior in the presence of different land-cover classes. The neural-network classifier (which is based on a radial basis function neural architecture) properly exploits the multitemporal features for producing accurate land-cover maps. Thanks to the effectiveness of the extracted features, the number of measures that can be provided as input to the classifier is significantly smaller than the number of available multitemporal images. This reduces the complexity of the neural architecture (and consequently increases the generalization capabilities of the classifier) and relaxes the requirements relating to the number of training patterns to be used for classifier learning. Experimental results (obtained on a multitemporal series of European Remote Sensing 1 satellite SAR images) confirm the effectiveness of the proposed system, which exhibits both high classification accuracy and good stability versus parameter settings. These results also point out that properly integrating a pattern recognition procedure (based on machine learning) with an accurate feature extraction phase (based on the SAR sensor physics understanding) represents an effective approach to SAR data analysis.

The effect of freezing and thawing on the microwave signatures of bare soil.

Abstract To study the effect of a frozen soil layer on the microwave signatures of bare soil, we carried out measurements on frozen and unfrozen fields in winter. Our ground-based radiometer — scatterometer system, RASAM, works at frequencies between 3 GHz and 11 GHz. The brightness temperature was measured at horizontal and vertical polarization, the backscattering coefficient at HH, VV, HV, and VH polarization, all at incidence angles from 0° to 70°. In addition, we measured soil parameters such as moisture, roughness, and texture. The results are subdivided into three sections. First the microwave parameters measured during two diurnal freeze — thaw cycles of the soil are shown. For thawing the soil has three layers wet/frozen/wet and therefore different microwave properties than for freezing. Second frozen soil (thickness of the frozen layer is larger than the penetration depth of the radiation) is compared with unfrozen soil. For the horizontal polarization we separate the reflectivity into the Fresnel reflectivity and a roughness factor. The active data are compared with the geometrical-optics model at the higher frequencies and with the small-perturbation model at the lower frequencies. In addition the data are used to determine the sensitivity of the microwave parameters to soil liquid water content. Third the growth of a frozen soil layer is monitored. These data are used to test layered media models. Due to the scale height of surface roughness, which is of the order of the penetration depth of the radiation, the models do not agree well with the measurements. We find much better fits with a semiempirical formula.

Nonuniform Ground Motion Monitoring With TerraSAR-X Persistent Scatterer Interferometry

In the past, the application of Persistent Scatterer Interferometry (PSI) was primarily possible in the case of slow (less than a few centimeters per year) uniform movements. In this paper, we show how PSI permits the monitoring of relatively fast (including rates up to > 50 cm/year) and nonuniform movements using TerraSAR-X repeat observations over deep-level mining. To enable this, parts of the PSI methodology were adapted to the special characteristics of the example studied. Apart from a description of the methodology used and the result achieved, error considerations and a validation of the result with in situ measurements are included.

Landuse mapping with ERS SAR interferometry

Two landuse maps and a forest map of three different areas in Europe were completed with ERS SAR interferometry. The test sites represent various geomorphological regions with different cover types. In this article, the mapping algorithms are presented, the results are summarized, and the potential and limitations of ERS SAR interferometry for landuse mapping are discussed. Overall, the results suggest that landuse classification accuracies on the order of 75% are possible with, in the best case, simultaneous forest and nonforest accuracies of around 80-85%. The presence of topography reduces the performance.

SAR interferometric and differential interferometric processing chain

The authors have developed a SAR and an interferometric processor suitable for all current SAR systems. The main modules of the processor are the Modular SAR Processor (MSP), the Interferometric SAR Processor (ISP), and the Differential Interferometry and Geocoding Module (DIFF&GEO). The potential and limitations of the selected algorithms and processing techniques are discussed. Typical results are shown.