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The persistent scatterer interferometry (PSI) is a well established monitoring technique for urban areas. It has been updated in order to process wide areas with the accepted characteristics in precision and resolution. Of course, the covered processing area now includes rural areas with a low persistent scatterer (PS) density. In order to bridge forested areas and water bodies, low quality and more distant PSs need to be included into the reference network. The development of the wide area product (WAP) succeeded to cope with the resulting difficulties resulting in spatial error propagation. In this paper, the developed WAP system is described and a processing example is presented.

Efficient estimation of the interferometric phase and complex correlation is fundamental for the full exploitation of SAR Interferometry capabilities . Particularly when combining interferometric measures arising both from distributed and concentrated point targets, the interferometric phase has to be correctly extracted in order to preserve its physical meaning and respect the homogeneity hypothesis that we assume when performing a coherent averaging . Recently, an amplitude-based algorithm for the adaptive multilooking of InSAR stacks was proposed, where it was shown that a comparison of the backscatter amplitude statistics is a suitable way to adaptively group and average the pixels in order to preserve the phase signatures of natural structures in the observed area.

In the Persistent Scatterer Interferometry relative height and deformation updates are estimated between nearby persistent scatterers (PSs). In practice, a reference network is established and the absolute values are estimated by integration. However, PSs can be mis-detected and relative measurements mis-estimated. As a consequence, the integration result depends on the integration path. Therefore, inconsistent measurements need to be eliminated. This paper presents our implemented integration technique which is based on a multithreaded Singular Value Decomposition. An advantage of our method is the straight forward error propagation assessment. As a result, the actual network can be improved by removing inaccurate point scatterers.

The measurement of displacement from SAR images, using either interferometric or correlation techniques, is always carried out from a comparison between two or more acquisitions separated in time. It is therefore necessary to evaluate the level of phase decorrelation between the two acquisitions in order to understand the quality of the measures that can be obtained. The change of radar resolution cells in time is known to be the main responsible of the gradual decorrelation of the interferometric phase. However, a model that physically describes this process, is at the moment not available. Exploiting the test sites from GITEWS and Exupery, German projects focussed on determination of geo-risks, an analysis of the decorrelation time constants was performed on SAR data from PALSAR, ASAR and TerraSAR-X. Time series of the coherence have been computed and compared with simple statistical models. The time constants were analyzed as a measure of temporal decorrelation, in order to forecast the precision of displacement measures also for future missions. The extracted parameters were finally compared with the type of land covering using optical data and land use maps in order to determine a qualitative relationship between them and extend their validity in a more global context.

Terrafirma is an ESA project and a services element in the framework of the Global Monitoring for Environment and Security (GMES) service element programme. Based on the Persistent Scatterer Interferometry (PSI), the project provides a Pan European ground motion hazard information service. The motion monitoring is supplied by commercial companies which act as Operational Service Providers (OSPs). A Product Validation Workgroup (PVW) has been formed for the validation and certification of the various motion data products which can provide different levels of value adding. Four OSPs operate processing chains for the generation of the basic level 1 product. These take part in a validation project which intends to demonstrate reliability and accuracy of the PSI motion monitoring. Amsterdam and Alkmaar in the Netherlands are the two test sites which are chosen for the comparison. Three data stacks - two from Envisat and one from ERS are processed independently by the OSPs in the course of the validation. Two strategies for the validation are foreseen in the validation project: on the one hand the Product Validation and on the other the Process Validation. Both are independent and complementary to each other. The Product Validation utilizes available ground truth information for the validation and assesses the final geocoded motion data. The Process Validation is a new type of PSI validation and compares the intermediate data in slant range only and consequently avoids problems of geocoding, misregistration and interpolation. This comparison is made by the German Aerospace Center (DLR) with assistance of the Institute of Geomatics (IG) which leads the overall validation project. The new validation approach and the intermediate validation results are reported.

Precise interferometric SAR measurements as well as characterization and information extraction of individual targets can be performed on natural or artificial point-like scatterers in SAR images. This is due, mainly, to the possibility to estimate their phase information very accurately, widely unaffected by speckle. Up to now, by means of two different techniques, two categories of such point-like scatterers have been treated: the Persistent Scatterers (PSs) and the Coherent Scatterers (CSs). On one hand, PSs are characterized by long term temporal stability and are detected using long time series of acquisitions. They enabled the development of geophysical applications as millimetric terrain motion monitoring and accurate DEM refinement. On the other hand, CSs can be detected on a single SAR image basis, by exploiting image spectral correlation properties, without any assumption of temporal stability. They are very promising concerning parameters extraction as LOS rotation angle and dielectric constants estimation. Due to the wide spectrum of informations provided by the combination of the two concepts in this paper we investigate the CSs temporal stability and the relationships existing between CSs and PSs based on the analysis of image time series.