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Development of new methodologies for the detection, measurement and on going monitoring of ground deformation using spaceborne SAR data

Persistent Scatterer Interferometric techniques are very powerful geodetic tools for land deformation monitoring that offer the typical advantages of the satellite remote sensing SAR (Synthetic Aperture Radar) systems : a wide coverage at a relatively high resolution. Those techniques are based on the analysis of a set of SAR images acquired over a given area. They overcome the decorrelation problem by identifying elements (in resolution cells) with a high quality returned SAR signal which remains stable in a series of interferograms. These techniques have been useful for the analysis of urban areas, where man-made objects produce good reflections that dominate over the background scattering, as well as in field areas where the density of infrastructures is more limited. Typically, PSI technique requires an approximate a priori temporal model for the detection of the deformation, even though characterizing the temporal evolution of a deformation is commonly one of the objectives of any study.This work is focused on a particular PSI technique, which is named Stable Point Network (SPN) and that it has been completely developed by Altamira Information in 2003. The work concisely outlines the main characteristics of this technique, and describes its main products: average deformation maps, deformation time series of the measured points, and the so-called maps of the residual topographic error, which are used to precisely geocode the PSI products. The main objectives of this PhD are the identification and analysis of the drawbacks of this processing chain, and the development of new tools and methodologies in order to overcome them. First, the performances of the SPN technique are examined and illustrated by means of practical cases (based on real test sites made with data coming from different sensors) and simulated scenarios.Thus, the main drawbacks of the technique are identified and discussed, such as the lack of automatic quality control parameters, the evaluation of the input data quality, the selection of good points for the measurements and the use of a functional model to unwrap the phases based on a linear deformation trend in time. Then, different enhancements are proposed. In particular, the automatic quality control of the coregistration procedure has been introduced through the analysis of the inter-pixel position of some natural point targets-like pixels identified within the images. The enhancements in the selection of the final points of measurements (the final PSI map) come by means of the analysis of the SAR signal signature of the strong targets presented within the image, in order to select only the center of the main lobe as point of measurement. The introduction of robustness within some critical steps of the technique is done by means of the analysis of the rotational of the estimates in close loops within a network of relative measurements, and by means of the implementation of a different integration methodology, which can be ran in parallel in order to compare it with the classical one. Finally, the main drawback of the technique, the use of a linear model for the detection of ground deformations, is addressed with the development of a new fitting methodology which allows possible change of trends within the analyzed time span. All those enhancements are evaluated with the use of real examples of applications and with simulated data. In particular, the new methodology for detecting non-linear ground deformations has been tested in the city of Paris, where a large stacking of ERS1/2 and ENVISAT SAR images are available. Those images are covering a very large time period of analysis at where some known non-linear ground deformations where occurring

Identiferoai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00638089
Date18 June 2010
CreatorsDuro, Javier
PublisherUniversité Paris-Est
Source SetsCCSD theses-EN-ligne, France
LanguageEnglish
Detected LanguageEnglish
TypePhD thesis

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