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Proceedings Paper

Reproduction of InSAR atmospheric signal using GPS data and atmospheric transport model
Author(s): Xiaogang Song; Mingsheng Liao
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Paper Abstract

Atmospheric water vapor effects represents a major limitation to accuracy in InSAR applications. a method based on GPS-ZWD timeseries and atmospheric transport model is developed to reproduce InSAR atmospheric signal so as to be applied to reduce atmospheric effects in interferogram. Firstly, based on correlation between wator vapor effect and topography, topography-dependent component of delay variation can be estimated by fitting a model of the vertical profile of neutral atmospheric delay to the GPS ZWD measurements at the SAR overpass time, then we use the fitting model and a SRTM DEM of imaged area to generate a map of altitude-dependent ZWD delay difference, which can be used to reduce topography-dependent atmospheric phase in InSAR interferogram. After removing the topography-dependent model, the residual fluctuations can be interpreted as turbulent variations of water vapor. Atmospheric transport model is introduced to transform GPS-ZWD timeseries around SAR overpass time into a spatially denser network of GPS-ZWD control points. The denser network of GPS-ZWD enable estimation of ZWD difference maps that better match the turbulently-mixed atmospheric phase distortions observed in the InSAR data. Experimental data analysis showed the method to seperately consider topography-dependent and turbulent mixing atmospheric effects effectively reproduce atmospheric signal in InSAR interferogram.

Paper Details

Date Published: 14 November 2007
PDF: 8 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67901K (14 November 2007); doi: 10.1117/12.748995
Show Author Affiliations
Xiaogang Song, Wuhan Univ. (China)
Mingsheng Liao, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications

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