This paper describes several geodetic studies that consolidate the reliability and precision of monitoring subsidence due to hydrocarbon production: the deployment of Integrated Geodetic Reference Stations (IGRS); the application of high resolution InSAR; the comparison of different GNSS processing methodologies; the implementation of an efficient InSAR stochastic model, and the framework of integrated geodetic processing (levelling, GNSS, InSAR). The advances that have been made are applicable for any other subsidence monitoring project.@en

InSAR data acquired from independent overlapping tracks can be exploited for a reliability assessment of the Persistent Scatterer InSAR (PS-InSAR) technique. This is obtained by means of the datum connection of multiple tracks, simultaneously evaluating the misclosures between multi-track PS-InSAR estimates. Due to a different viewing geometry, many of the detected PS will physically not be the same. However, their estimates may still refer to the same deformation signal. The existence of independent observations of the same deformation signal provides a powerful tool to increase the redundancy and evaluate the reliability. The datum connection can be subdivided in two steps. The first step consists of the conversion of PS locations to a common datum. Secondly, the PS-InSAR parameter estimates (velocities, displacements, heights) are connected. In stead of the conventional approach of separately geocoding each track, we propose the use of a common radar datum defined by the acquisition geometry of the 'master track'. Multi-track datum connection has been applied in the Groningen region, the Netherlands, which is affected by subsidence due to gas extraction with displacement rates up to 7 mm/year. The main reservoir is (partly) visible in 6 independent overlapping ERS tracks from 1992 (ascending and descending). Datum connection resulted in a consistent set of PS-InSAR deformation estimates. Additionally, the deformation signal was decomposed in horizontal and vertical movements, utilizing the different viewing geometries of the tracks.@en

PS-InSAR has proven to be an accurate and efficient technique for the joint estimation of topographic and displacement signal from stacked interferometric combinations. In this contribution a new method for PS-Insert processing is introduced, which enables the recursive estimation of parameters of interest. The method is based on the ILSQ PS-InSAR concept and makes use of the estimation vector and corresponding variance-covariance matrix of the initial estimation epoch. The presented methodology systematically adds a new acquisition (or set of acquisitions) to the existing stack, updates the solution of the previous run, and analyzes whether the behaviour of the (pre-) selected points fits the expected one. This contribution focuses on a mathematical framework, rather then on specific applicational problems. Nevertheless, the performed numerical analysis on simulated data sets is analyzed and discussed, which shows that the preset aims of the recursive PS-InSAR estimation technique is achieved.@en

In interferometric data coregistration, both the windows and polynomial approaches influence the offsets calculation and coregistration results because of the topography in the area of a SAR image. In this paper, by using precise orbit data of ERS satellite and topographic information, we analyze qualitatively the relation between offsets difference and several influence factors as elevation, distance from near range to far range and perpendicular baseline and the selection of the order of polynomial in different topographies. The results show the DEM influence in range direction has a direct ratio relation with the elevation and perpendicular baseline but an inverse ratio relation with the distance from near to far range, the DEM influence in azimuth direction has a direct ratio relation with the elevation but small correlation with the perpendicular baseline and the distance from near to far range. Moreover, in the polynomial approach different orders of the polynomial are needed in different topographies to achieve more accurate offset result.@en

In this paper, the time series multi-image stack processing technique is implemented based on the ERS-1, ERS-2 SAR data set of cities of Las Vegas in America. A single master approach is used in the stack data processing based on the permanent scatterers processing technique invented by Ferretti et al. [1,2]. After the differential phase model establishment and stable points selection, linear subsidence velocity and digital elevation model errors are estimated, non-linear subsidence velocity and atmospheric artifacts related to each SAR acquisition are separated, so a land subsidence history covering all the SAR data acquisitions in each city can be achieved. In our research, more test data in cities of China will be implemented in the next step.

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