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Geodetic time series analysis in ear...

Montillet, Jean-Philippe.

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Geodetic time series analysis in earth sciences

Record Type:	Electronic resources : Monograph/item
Title/Author:	Geodetic time series analysis in earth sciences/ edited by Jean-Philippe Montillet, Machiel S. Bos.
other author:	Montillet, Jean-Philippe.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xxi, 422 p. :ill., digital ;24 cm.
[NT 15003449]:	The Art and Science of Trajectory Modelling -- Introduction to Geodetic Time Series Analysis -- Markov Chain Monte Carlo and The Application to Geodetic Time Series Analysis -- Introduction to Dynamic Linear Models for Time Series Analysis -- Fast Statistical Approaches to Geodetic Time Series Analysis -- Least Squares Contribution to Geodetic Time Series Analysis -- Modelling the GNSS Time Series: Different Approaches to Extract Seasonal Signals -- Stochastic modelling of geophysical signal constituents within a Kalman Filter framework -- Filtering of GPS Time Series Using Geophysical Models and Common Mode Error Analysis -- Comparison of Spacewise and Timewise Methods for GRACE Gravity Field Recovery -- Estimation of the Vertical Land Motion from GNSS Time Series and Application in Quantifying Sea-Level Rise -- Time Series Analysis of Rapid GNSS Measurements for Quasi-Static and Dynamic Bridge Monitoring -- Conclusions and Future challenges in Geodetic Time Series Analysis.
Contained By:	Springer Nature eBook
Subject:	Geodesy. -
Online resource:	https://doi.org/10.1007/978-3-030-21718-1
ISBN:	9783030217181

Geodetic time series analysis in earth sciences
Geodetic time series analysis in earth sciences[electronic resource] /edited by Jean-Philippe Montillet, Machiel S. Bos. - Cham :Springer International Publishing :2020. - xxi, 422 p. :ill., digital ;24 cm. - Springer geophysics,2364-9119. - Springer geophysics..

The Art and Science of Trajectory Modelling -- Introduction to Geodetic Time Series Analysis -- Markov Chain Monte Carlo and The Application to Geodetic Time Series Analysis -- Introduction to Dynamic Linear Models for Time Series Analysis -- Fast Statistical Approaches to Geodetic Time Series Analysis -- Least Squares Contribution to Geodetic Time Series Analysis -- Modelling the GNSS Time Series: Different Approaches to Extract Seasonal Signals -- Stochastic modelling of geophysical signal constituents within a Kalman Filter framework -- Filtering of GPS Time Series Using Geophysical Models and Common Mode Error Analysis -- Comparison of Spacewise and Timewise Methods for GRACE Gravity Field Recovery -- Estimation of the Vertical Land Motion from GNSS Time Series and Application in Quantifying Sea-Level Rise -- Time Series Analysis of Rapid GNSS Measurements for Quasi-Static and Dynamic Bridge Monitoring -- Conclusions and Future challenges in Geodetic Time Series Analysis.

This book provides an essential appraisal of the recent advances in technologies, mathematical models and computational software used by those working with geodetic data. It explains the latest methods in processing and analyzing geodetic time series data from various space missions (i.e. GNSS, GRACE) and other technologies (i.e. tide gauges), using the most recent mathematical models. The book provides practical examples of how to apply these models to estimate seal level rise as well as rapid and evolving land motion changes due to gravity (ice sheet loss) and earthquakes respectively. It also provides a necessary overview of geodetic software and where to obtain them.

ISBN: 9783030217181

Standard No.: 10.1007/978-3-030-21718-1doiSubjects--Topical Terms:

550741
Geodesy.

LC Class. No.: QB281 / .G46 2020

Dewey Class. No.: 526.1

Geodetic time series analysis in earth sciences
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245 0 0 $a Geodetic time series analysis in earth sciences $h [electronic resource] / $c edited by Jean-Philippe Montillet, Machiel S. Bos.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xxi, 422 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer geophysics, $x 2364-9119
505 0 $a The Art and Science of Trajectory Modelling -- Introduction to Geodetic Time Series Analysis -- Markov Chain Monte Carlo and The Application to Geodetic Time Series Analysis -- Introduction to Dynamic Linear Models for Time Series Analysis -- Fast Statistical Approaches to Geodetic Time Series Analysis -- Least Squares Contribution to Geodetic Time Series Analysis -- Modelling the GNSS Time Series: Different Approaches to Extract Seasonal Signals -- Stochastic modelling of geophysical signal constituents within a Kalman Filter framework -- Filtering of GPS Time Series Using Geophysical Models and Common Mode Error Analysis -- Comparison of Spacewise and Timewise Methods for GRACE Gravity Field Recovery -- Estimation of the Vertical Land Motion from GNSS Time Series and Application in Quantifying Sea-Level Rise -- Time Series Analysis of Rapid GNSS Measurements for Quasi-Static and Dynamic Bridge Monitoring -- Conclusions and Future challenges in Geodetic Time Series Analysis.
520 $a This book provides an essential appraisal of the recent advances in technologies, mathematical models and computational software used by those working with geodetic data. It explains the latest methods in processing and analyzing geodetic time series data from various space missions (i.e. GNSS, GRACE) and other technologies (i.e. tide gauges), using the most recent mathematical models. The book provides practical examples of how to apply these models to estimate seal level rise as well as rapid and evolving land motion changes due to gravity (ice sheet loss) and earthquakes respectively. It also provides a necessary overview of geodetic software and where to obtain them.
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650 2 4 $a Geophysics and Environmental Physics. $3 1530865
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 1005896
700 1 $a Montillet, Jean-Philippe. $3 3529701
700 1 $a Bos, Machiel S. $3 3529702
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830 0 $a Springer geophysics. $3 1620330
856 4 0 $u https://doi.org/10.1007/978-3-030-21718-1
950 $a Earth and Environmental Science (SpringerNature-11646)