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Stepwise Approach to InSAR Processing of Multitemporal Datasets

Alberto Refice(1) and Fabio Bovenga(2)

(1) CNR, Via Amendola 166/5, 70126 Bari, Italy
(2) Politecnico di Bari, Via Amendola 173, 70126 Bari, Italy


In the last years it has been shown that processing of multi-temporal stacks of SAR images can improve the capability of microwave sensors to estimate ground displacements [1,2,3]. Among the most important applications of this approach is the monitoring of millimetric surface movements related to natural hazards such as earthquakes, landslides, subsidences, etc. However, there are two conflicting processing aspects that must be taken into account, namely the huge computational load and the high accuracy requirements. A typical multitemporal ERS SAR dataset is composed of several tens of radar images; for each image, several conventional steps (focusing, coregistration, interferogram generation, flat earth phase removal, etc.) have to be performed. This time-consuming work can be optimized by reducing the user intervention, by means of a fully automatic implementation of the aforementioned steps. However, the large temporal and geometric baselines spanned by some of the processed interferometric pairs introduce strong decorrelation, which forces the user to interact often with the processing chain, especially in the coregistration step, to preserve the results accuracy. This is mainly due to the conventional processing methodology, which involves deriving each interferogram with respect to one single “master” image. In this paper, an alternate approach to process multi-temporal InSAR datasets is investigated. The method consists in splitting up the processing step for each image pair made of the single “master” and one of the several “slaves”, into several partial steps which exploit acquisitions separated by small temporal and geometric baselines. Successively, these steps are integrated. Each partial step is affected by a lower contribution of decorrelation noise with respect to the “single master” case, allowing a fully automatic and accurate procedure with no user intervention. Some experimental tests and results are provided with reference to an ERS-1/2 dataset over the landslide site of Caramanico Terme, involved in the ESA AO3-313 project.

References [1] O. Mora, R. Lanari, J. J Mallorqui, P. Berardino, E. Sansosti, A new Algorithm for Monitoring Localized Deformation Phenomena Based on Small Baseline Differential SAR Interferograms, IGARSS 2002 24th Canadian Symposium on Remote Sensing. [2] M. Costantini, F. Malvarosa, F. Minati, L. Pietranera and G. Milillo, A Three-dimensional Phase Unwrapping Algorithm for Processing of Multitemporal SAR Interferometric Measurements, IGARSS 2002 24th Canadian Symposium on Remote Sensing. [3] A. Ferretti, C. Prati, F. Rocca, “Permanent Scatterers in SAR Interferometry”, IEEE Transactions on Geoscience and Remote Sensing”, vol.39, No.1, pp. 8-20, Jan. 2001.


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Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry