A Quadtree InSAR Data Reduction Method Based on Covariance Function

Abstract

Abstract:

A major problem in inversion of deformation mechanism using InSAR data is that the InSAR results often contain thousands to millions of data points. Furthermore, there always exist errors and even some blunders, which make the data inversion be lower efficient and lower reliable. Thus, we propose an adaptive quadtree decomposition method for InSAR data reduction in order to reduce the data numbers without losing the significant information about the deformation. The two important parameters of quadtree decomposition by covariance function is determined ,which is eatablished by taking account of the physical spatial crrelation of InSAR data. The algorithm can preserve details of deformation as much as possible and achieve efficient data reduction. This method is evaluated with InSAR data over Xi’an land subsidence. The results indicate that the algorithm proposed in this manuscript can not only reduce InSAR data number efficiently under a very good preservation of deformation signal, but can eliminate the noise of deformation results efficiently.

Key words: quadtree, data reduction, spatial correlation, covariance function

CLC Number:

P237

References

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