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Geodetic Time Series Analysis in Earth Sciences

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Cover of 'Geodetic Time Series Analysis in Earth Sciences'

Table of Contents

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    Book Overview
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    Chapter 1 The Art and Science of Trajectory Modelling
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    Chapter 2 Introduction to Geodetic Time Series Analysis
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    Chapter 3 Markov Chain Monte Carlo and the Application to Geodetic Time Series Analysis
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    Chapter 4 Introduction to Dynamic Linear Models for Time Series Analysis
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    Chapter 5 Fast Statistical Approaches to Geodetic Time Series Analysis
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    Chapter 6 Least Squares Contribution to Geodetic Time Series Analysis
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    Chapter 7 Modelling the GNSS Time Series: Different Approaches to Extract Seasonal Signals
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    Chapter 8 Stochastic Modelling of Geophysical Signal Constituents Within a Kalman Filter Framework
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    Chapter 9 Filtering of GPS Time Series Using Geophysical Models and Common Mode Error Analysis
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    Chapter 10 Comparison of Spacewise and Timewise Methods for GRACE Gravity Field Recovery
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    Chapter 11 Estimation of the Vertical Land Motion from GNSS Time Series and Application in Quantifying Sea-Level Rise
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    Chapter 12 Time Series Analysis of Rapid GNSS Measurements for Quasi-static and Dynamic Bridge Monitoring
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    Chapter 13 Conclusions and Future Challenges in Geodetic Time Series Analysis
Attention for Chapter 8: Stochastic Modelling of Geophysical Signal Constituents Within a Kalman Filter Framework
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Chapter title
Stochastic Modelling of Geophysical Signal Constituents Within a Kalman Filter Framework
Chapter number 8
Book title
Geodetic Time Series Analysis in Earth Sciences
Published by
Springer, Cham, August 2019
DOI 10.1007/978-3-030-21718-1_8
Book ISBNs
978-3-03-021717-4, 978-3-03-021718-1
Authors

Olga Engels, Engels, Olga

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 100%
Readers by discipline Count As %
Earth and Planetary Sciences 1 100%

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