Analysis of GPS Measurements in Eastern Canada Using Principal Component Analysis
Abstract Continuous Global Positioning System (CGPS) position time series from eastern North America constrain the pattern and magnitude of regional crustal deformation. Initial analysis delineates consistent uplift patterns, as expected from glacial isostatic adjustment (GIA) predictions, but the a...
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| Autor*in: |
Tiampo, K. F. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2011 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Basel AG 2011 |
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| Übergeordnetes Werk: |
Enthalten in: Pure and applied geophysics - SP Birkhäuser Verlag Basel, 1964, 169(2011), 8 vom: 17. Nov., Seite 1483-1506 |
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| Übergeordnetes Werk: |
volume:169 ; year:2011 ; number:8 ; day:17 ; month:11 ; pages:1483-1506 |
| Links: |
|---|
| DOI / URN: |
10.1007/s00024-011-0420-1 |
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OLC2069495620 |
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| 520 | |a Abstract Continuous Global Positioning System (CGPS) position time series from eastern North America constrain the pattern and magnitude of regional crustal deformation. Initial analysis delineates consistent uplift patterns, as expected from glacial isostatic adjustment (GIA) predictions, but the associated horizontal deformation is not definitive, in part due to the short time periods for a significant number of the available stations. We employ an eigenpattern decomposition in order to define a unique, finite set of deformation patterns for this continuous GPS data. Similar in nature to the empirical orthogonal functions historically employed in the analysis of atmospheric and oceanographic phenomena, the method derives the eigenvalues and eigenstates from the diagonalization of the correlation matrix using a Karhunen–Loeve expansion (KLE). The KLE technique is used to identify the important modes in both time and space for the CGPS data, modes that potentially include signals such as horizontal and vertical GIA, tectonic strain, and seasonal effects. Here we filter both the vertical and horizontal velocity patterns on different spatiotemporal scales in order to study the potential geophysical sources, after the removal of correlated and random noise. The method is successful in disaggregating the linear vertical signal from more variable and less spatially correlated signals. The vertical and horizontal results are compared to the predictions of the ICE-3G GIA loading model with a number of plausible mantle viscosity profiles. The horizontal velocity analysis allows for qualitative differentiation between several potential GIA models and suggests that, with longer time series, this technique can be employed to remove correlated noise and improve estimates of crustal strain patterns and their sources. | ||
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10.1007/s00024-011-0420-1 doi (DE-627)OLC2069495620 (DE-He213)s00024-011-0420-1-p DE-627 ger DE-627 rakwb eng 550 VZ 550 VZ 16,13 ssgn Tiampo, K. F. verfasserin aut Analysis of GPS Measurements in Eastern Canada Using Principal Component Analysis 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Basel AG 2011 Abstract Continuous Global Positioning System (CGPS) position time series from eastern North America constrain the pattern and magnitude of regional crustal deformation. Initial analysis delineates consistent uplift patterns, as expected from glacial isostatic adjustment (GIA) predictions, but the associated horizontal deformation is not definitive, in part due to the short time periods for a significant number of the available stations. We employ an eigenpattern decomposition in order to define a unique, finite set of deformation patterns for this continuous GPS data. Similar in nature to the empirical orthogonal functions historically employed in the analysis of atmospheric and oceanographic phenomena, the method derives the eigenvalues and eigenstates from the diagonalization of the correlation matrix using a Karhunen–Loeve expansion (KLE). The KLE technique is used to identify the important modes in both time and space for the CGPS data, modes that potentially include signals such as horizontal and vertical GIA, tectonic strain, and seasonal effects. Here we filter both the vertical and horizontal velocity patterns on different spatiotemporal scales in order to study the potential geophysical sources, after the removal of correlated and random noise. The method is successful in disaggregating the linear vertical signal from more variable and less spatially correlated signals. The vertical and horizontal results are compared to the predictions of the ICE-3G GIA loading model with a number of plausible mantle viscosity profiles. The horizontal velocity analysis allows for qualitative differentiation between several potential GIA models and suggests that, with longer time series, this technique can be employed to remove correlated noise and improve estimates of crustal strain patterns and their sources. Global Position System Global Position System Data Global Position System Station Glacial Isostatic Adjustment Hinge Line Mazzotti, S. aut James, T. S. aut Enthalten in Pure and applied geophysics SP Birkhäuser Verlag Basel, 1964 169(2011), 8 vom: 17. Nov., Seite 1483-1506 (DE-627)129538353 (DE-600)216719-0 (DE-576)014971038 0033-4553 nnns volume:169 year:2011 number:8 day:17 month:11 pages:1483-1506 https://doi.org/10.1007/s00024-011-0420-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_21 GBV_ILN_22 GBV_ILN_40 GBV_ILN_70 GBV_ILN_267 GBV_ILN_601 GBV_ILN_4028 GBV_ILN_4155 GBV_ILN_4277 AR 169 2011 8 17 11 1483-1506 |
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10.1007/s00024-011-0420-1 doi (DE-627)OLC2069495620 (DE-He213)s00024-011-0420-1-p DE-627 ger DE-627 rakwb eng 550 VZ 550 VZ 16,13 ssgn Tiampo, K. F. verfasserin aut Analysis of GPS Measurements in Eastern Canada Using Principal Component Analysis 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Basel AG 2011 Abstract Continuous Global Positioning System (CGPS) position time series from eastern North America constrain the pattern and magnitude of regional crustal deformation. Initial analysis delineates consistent uplift patterns, as expected from glacial isostatic adjustment (GIA) predictions, but the associated horizontal deformation is not definitive, in part due to the short time periods for a significant number of the available stations. We employ an eigenpattern decomposition in order to define a unique, finite set of deformation patterns for this continuous GPS data. Similar in nature to the empirical orthogonal functions historically employed in the analysis of atmospheric and oceanographic phenomena, the method derives the eigenvalues and eigenstates from the diagonalization of the correlation matrix using a Karhunen–Loeve expansion (KLE). The KLE technique is used to identify the important modes in both time and space for the CGPS data, modes that potentially include signals such as horizontal and vertical GIA, tectonic strain, and seasonal effects. Here we filter both the vertical and horizontal velocity patterns on different spatiotemporal scales in order to study the potential geophysical sources, after the removal of correlated and random noise. The method is successful in disaggregating the linear vertical signal from more variable and less spatially correlated signals. The vertical and horizontal results are compared to the predictions of the ICE-3G GIA loading model with a number of plausible mantle viscosity profiles. The horizontal velocity analysis allows for qualitative differentiation between several potential GIA models and suggests that, with longer time series, this technique can be employed to remove correlated noise and improve estimates of crustal strain patterns and their sources. Global Position System Global Position System Data Global Position System Station Glacial Isostatic Adjustment Hinge Line Mazzotti, S. aut James, T. S. aut Enthalten in Pure and applied geophysics SP Birkhäuser Verlag Basel, 1964 169(2011), 8 vom: 17. Nov., Seite 1483-1506 (DE-627)129538353 (DE-600)216719-0 (DE-576)014971038 0033-4553 nnns volume:169 year:2011 number:8 day:17 month:11 pages:1483-1506 https://doi.org/10.1007/s00024-011-0420-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_21 GBV_ILN_22 GBV_ILN_40 GBV_ILN_70 GBV_ILN_267 GBV_ILN_601 GBV_ILN_4028 GBV_ILN_4155 GBV_ILN_4277 AR 169 2011 8 17 11 1483-1506 |
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10.1007/s00024-011-0420-1 doi (DE-627)OLC2069495620 (DE-He213)s00024-011-0420-1-p DE-627 ger DE-627 rakwb eng 550 VZ 550 VZ 16,13 ssgn Tiampo, K. F. verfasserin aut Analysis of GPS Measurements in Eastern Canada Using Principal Component Analysis 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Basel AG 2011 Abstract Continuous Global Positioning System (CGPS) position time series from eastern North America constrain the pattern and magnitude of regional crustal deformation. Initial analysis delineates consistent uplift patterns, as expected from glacial isostatic adjustment (GIA) predictions, but the associated horizontal deformation is not definitive, in part due to the short time periods for a significant number of the available stations. We employ an eigenpattern decomposition in order to define a unique, finite set of deformation patterns for this continuous GPS data. Similar in nature to the empirical orthogonal functions historically employed in the analysis of atmospheric and oceanographic phenomena, the method derives the eigenvalues and eigenstates from the diagonalization of the correlation matrix using a Karhunen–Loeve expansion (KLE). The KLE technique is used to identify the important modes in both time and space for the CGPS data, modes that potentially include signals such as horizontal and vertical GIA, tectonic strain, and seasonal effects. Here we filter both the vertical and horizontal velocity patterns on different spatiotemporal scales in order to study the potential geophysical sources, after the removal of correlated and random noise. The method is successful in disaggregating the linear vertical signal from more variable and less spatially correlated signals. The vertical and horizontal results are compared to the predictions of the ICE-3G GIA loading model with a number of plausible mantle viscosity profiles. The horizontal velocity analysis allows for qualitative differentiation between several potential GIA models and suggests that, with longer time series, this technique can be employed to remove correlated noise and improve estimates of crustal strain patterns and their sources. Global Position System Global Position System Data Global Position System Station Glacial Isostatic Adjustment Hinge Line Mazzotti, S. aut James, T. S. aut Enthalten in Pure and applied geophysics SP Birkhäuser Verlag Basel, 1964 169(2011), 8 vom: 17. Nov., Seite 1483-1506 (DE-627)129538353 (DE-600)216719-0 (DE-576)014971038 0033-4553 nnns volume:169 year:2011 number:8 day:17 month:11 pages:1483-1506 https://doi.org/10.1007/s00024-011-0420-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_21 GBV_ILN_22 GBV_ILN_40 GBV_ILN_70 GBV_ILN_267 GBV_ILN_601 GBV_ILN_4028 GBV_ILN_4155 GBV_ILN_4277 AR 169 2011 8 17 11 1483-1506 |
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10.1007/s00024-011-0420-1 doi (DE-627)OLC2069495620 (DE-He213)s00024-011-0420-1-p DE-627 ger DE-627 rakwb eng 550 VZ 550 VZ 16,13 ssgn Tiampo, K. F. verfasserin aut Analysis of GPS Measurements in Eastern Canada Using Principal Component Analysis 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Basel AG 2011 Abstract Continuous Global Positioning System (CGPS) position time series from eastern North America constrain the pattern and magnitude of regional crustal deformation. Initial analysis delineates consistent uplift patterns, as expected from glacial isostatic adjustment (GIA) predictions, but the associated horizontal deformation is not definitive, in part due to the short time periods for a significant number of the available stations. We employ an eigenpattern decomposition in order to define a unique, finite set of deformation patterns for this continuous GPS data. Similar in nature to the empirical orthogonal functions historically employed in the analysis of atmospheric and oceanographic phenomena, the method derives the eigenvalues and eigenstates from the diagonalization of the correlation matrix using a Karhunen–Loeve expansion (KLE). The KLE technique is used to identify the important modes in both time and space for the CGPS data, modes that potentially include signals such as horizontal and vertical GIA, tectonic strain, and seasonal effects. Here we filter both the vertical and horizontal velocity patterns on different spatiotemporal scales in order to study the potential geophysical sources, after the removal of correlated and random noise. The method is successful in disaggregating the linear vertical signal from more variable and less spatially correlated signals. The vertical and horizontal results are compared to the predictions of the ICE-3G GIA loading model with a number of plausible mantle viscosity profiles. The horizontal velocity analysis allows for qualitative differentiation between several potential GIA models and suggests that, with longer time series, this technique can be employed to remove correlated noise and improve estimates of crustal strain patterns and their sources. Global Position System Global Position System Data Global Position System Station Glacial Isostatic Adjustment Hinge Line Mazzotti, S. aut James, T. S. aut Enthalten in Pure and applied geophysics SP Birkhäuser Verlag Basel, 1964 169(2011), 8 vom: 17. Nov., Seite 1483-1506 (DE-627)129538353 (DE-600)216719-0 (DE-576)014971038 0033-4553 nnns volume:169 year:2011 number:8 day:17 month:11 pages:1483-1506 https://doi.org/10.1007/s00024-011-0420-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_21 GBV_ILN_22 GBV_ILN_40 GBV_ILN_70 GBV_ILN_267 GBV_ILN_601 GBV_ILN_4028 GBV_ILN_4155 GBV_ILN_4277 AR 169 2011 8 17 11 1483-1506 |
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10.1007/s00024-011-0420-1 doi (DE-627)OLC2069495620 (DE-He213)s00024-011-0420-1-p DE-627 ger DE-627 rakwb eng 550 VZ 550 VZ 16,13 ssgn Tiampo, K. F. verfasserin aut Analysis of GPS Measurements in Eastern Canada Using Principal Component Analysis 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Basel AG 2011 Abstract Continuous Global Positioning System (CGPS) position time series from eastern North America constrain the pattern and magnitude of regional crustal deformation. Initial analysis delineates consistent uplift patterns, as expected from glacial isostatic adjustment (GIA) predictions, but the associated horizontal deformation is not definitive, in part due to the short time periods for a significant number of the available stations. We employ an eigenpattern decomposition in order to define a unique, finite set of deformation patterns for this continuous GPS data. Similar in nature to the empirical orthogonal functions historically employed in the analysis of atmospheric and oceanographic phenomena, the method derives the eigenvalues and eigenstates from the diagonalization of the correlation matrix using a Karhunen–Loeve expansion (KLE). The KLE technique is used to identify the important modes in both time and space for the CGPS data, modes that potentially include signals such as horizontal and vertical GIA, tectonic strain, and seasonal effects. Here we filter both the vertical and horizontal velocity patterns on different spatiotemporal scales in order to study the potential geophysical sources, after the removal of correlated and random noise. The method is successful in disaggregating the linear vertical signal from more variable and less spatially correlated signals. The vertical and horizontal results are compared to the predictions of the ICE-3G GIA loading model with a number of plausible mantle viscosity profiles. The horizontal velocity analysis allows for qualitative differentiation between several potential GIA models and suggests that, with longer time series, this technique can be employed to remove correlated noise and improve estimates of crustal strain patterns and their sources. Global Position System Global Position System Data Global Position System Station Glacial Isostatic Adjustment Hinge Line Mazzotti, S. aut James, T. S. aut Enthalten in Pure and applied geophysics SP Birkhäuser Verlag Basel, 1964 169(2011), 8 vom: 17. Nov., Seite 1483-1506 (DE-627)129538353 (DE-600)216719-0 (DE-576)014971038 0033-4553 nnns volume:169 year:2011 number:8 day:17 month:11 pages:1483-1506 https://doi.org/10.1007/s00024-011-0420-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_21 GBV_ILN_22 GBV_ILN_40 GBV_ILN_70 GBV_ILN_267 GBV_ILN_601 GBV_ILN_4028 GBV_ILN_4155 GBV_ILN_4277 AR 169 2011 8 17 11 1483-1506 |
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Analysis of GPS Measurements in Eastern Canada Using Principal Component Analysis |
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Analysis of GPS Measurements in Eastern Canada Using Principal Component Analysis |
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analysis of gps measurements in eastern canada using principal component analysis |
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Analysis of GPS Measurements in Eastern Canada Using Principal Component Analysis |
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Abstract Continuous Global Positioning System (CGPS) position time series from eastern North America constrain the pattern and magnitude of regional crustal deformation. Initial analysis delineates consistent uplift patterns, as expected from glacial isostatic adjustment (GIA) predictions, but the associated horizontal deformation is not definitive, in part due to the short time periods for a significant number of the available stations. We employ an eigenpattern decomposition in order to define a unique, finite set of deformation patterns for this continuous GPS data. Similar in nature to the empirical orthogonal functions historically employed in the analysis of atmospheric and oceanographic phenomena, the method derives the eigenvalues and eigenstates from the diagonalization of the correlation matrix using a Karhunen–Loeve expansion (KLE). The KLE technique is used to identify the important modes in both time and space for the CGPS data, modes that potentially include signals such as horizontal and vertical GIA, tectonic strain, and seasonal effects. Here we filter both the vertical and horizontal velocity patterns on different spatiotemporal scales in order to study the potential geophysical sources, after the removal of correlated and random noise. The method is successful in disaggregating the linear vertical signal from more variable and less spatially correlated signals. The vertical and horizontal results are compared to the predictions of the ICE-3G GIA loading model with a number of plausible mantle viscosity profiles. The horizontal velocity analysis allows for qualitative differentiation between several potential GIA models and suggests that, with longer time series, this technique can be employed to remove correlated noise and improve estimates of crustal strain patterns and their sources. © Springer Basel AG 2011 |
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Abstract Continuous Global Positioning System (CGPS) position time series from eastern North America constrain the pattern and magnitude of regional crustal deformation. Initial analysis delineates consistent uplift patterns, as expected from glacial isostatic adjustment (GIA) predictions, but the associated horizontal deformation is not definitive, in part due to the short time periods for a significant number of the available stations. We employ an eigenpattern decomposition in order to define a unique, finite set of deformation patterns for this continuous GPS data. Similar in nature to the empirical orthogonal functions historically employed in the analysis of atmospheric and oceanographic phenomena, the method derives the eigenvalues and eigenstates from the diagonalization of the correlation matrix using a Karhunen–Loeve expansion (KLE). The KLE technique is used to identify the important modes in both time and space for the CGPS data, modes that potentially include signals such as horizontal and vertical GIA, tectonic strain, and seasonal effects. Here we filter both the vertical and horizontal velocity patterns on different spatiotemporal scales in order to study the potential geophysical sources, after the removal of correlated and random noise. The method is successful in disaggregating the linear vertical signal from more variable and less spatially correlated signals. The vertical and horizontal results are compared to the predictions of the ICE-3G GIA loading model with a number of plausible mantle viscosity profiles. The horizontal velocity analysis allows for qualitative differentiation between several potential GIA models and suggests that, with longer time series, this technique can be employed to remove correlated noise and improve estimates of crustal strain patterns and their sources. © Springer Basel AG 2011 |
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Abstract Continuous Global Positioning System (CGPS) position time series from eastern North America constrain the pattern and magnitude of regional crustal deformation. Initial analysis delineates consistent uplift patterns, as expected from glacial isostatic adjustment (GIA) predictions, but the associated horizontal deformation is not definitive, in part due to the short time periods for a significant number of the available stations. We employ an eigenpattern decomposition in order to define a unique, finite set of deformation patterns for this continuous GPS data. Similar in nature to the empirical orthogonal functions historically employed in the analysis of atmospheric and oceanographic phenomena, the method derives the eigenvalues and eigenstates from the diagonalization of the correlation matrix using a Karhunen–Loeve expansion (KLE). The KLE technique is used to identify the important modes in both time and space for the CGPS data, modes that potentially include signals such as horizontal and vertical GIA, tectonic strain, and seasonal effects. Here we filter both the vertical and horizontal velocity patterns on different spatiotemporal scales in order to study the potential geophysical sources, after the removal of correlated and random noise. The method is successful in disaggregating the linear vertical signal from more variable and less spatially correlated signals. The vertical and horizontal results are compared to the predictions of the ICE-3G GIA loading model with a number of plausible mantle viscosity profiles. The horizontal velocity analysis allows for qualitative differentiation between several potential GIA models and suggests that, with longer time series, this technique can be employed to remove correlated noise and improve estimates of crustal strain patterns and their sources. © Springer Basel AG 2011 |
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