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Spatiotemporal filtering using principal component analysis and Karhunen-Loeve expansion approaches for regional GPS network analysis

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dc.contributor.author Dong, D.
dc.contributor.author Fang, P.
dc.contributor.author Bock, F.
dc.contributor.author Webb, F.
dc.contributor.author Prawirondirdjo, L.
dc.contributor.author Kedar, S.
dc.contributor.author Jamason, P.
dc.date.accessioned 2007-07-02T22:59:52Z
dc.date.available 2007-07-02T22:59:52Z
dc.date.issued 2006-03-09
dc.identifier.citation Journal of Geophysical Research, Vol. 110, B03405, doi: 10.1029/2005JB003806, 2006 en
dc.identifier.clearanceno 05-1177
dc.identifier.uri http://hdl.handle.net/2014/40310
dc.description.abstract Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns. en
dc.description.sponsorship NASA/JPL en
dc.format.extent 1938503 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US en
dc.publisher The American Geophysical Union en
dc.subject Principal component analysis (PCA) en
dc.subject spatiotemporal filtering en
dc.subject displacement en
dc.subject GPS
dc.title Spatiotemporal filtering using principal component analysis and Karhunen-Loeve expansion approaches for regional GPS network analysis en
dc.type Article en


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