Titlebook: Geodetic Time Series Analysis in Earth Sciences; Jean-Philippe Montillet,Machiel S. Bos Book 2020 Springer Nature Switzerland AG 2020 GNSS

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书目名称Geodetic Time Series Analysis in Earth Sciences影响因子(影响力)




书目名称Geodetic Time Series Analysis in Earth Sciences影响因子(影响力)学科排名




书目名称Geodetic Time Series Analysis in Earth Sciences网络公开度




书目名称Geodetic Time Series Analysis in Earth Sciences网络公开度学科排名




书目名称Geodetic Time Series Analysis in Earth Sciences被引频次




书目名称Geodetic Time Series Analysis in Earth Sciences被引频次学科排名




书目名称Geodetic Time Series Analysis in Earth Sciences年度引用




书目名称Geodetic Time Series Analysis in Earth Sciences年度引用学科排名




书目名称Geodetic Time Series Analysis in Earth Sciences读者反馈




书目名称Geodetic Time Series Analysis in Earth Sciences读者反馈学科排名

ARM

https://doi.org/10.1007/978-3-642-86311-0he noise in orbital velocity corrupts the potential difference observables, and respectively the estimate of the gravity field. Although, variational equations perform better, it is important that both positions and range rates are combined and they are properly weighted in solving normal equations.

暂时休息

Filtering of GPS Time Series Using Geophysical Models and Common Mode Error Analysis,ow the output of various surface loading models can be used to reduce the scattering of the time series. Furthermore, Common Mode and Principal Component Analysis may be applied which again causes a further reduction of the noise and in this way could produce a more accurate estimate of the trajectory model parameters.

Reservation

Comparison of Spacewise and Timewise Methods for GRACE Gravity Field Recovery,he noise in orbital velocity corrupts the potential difference observables, and respectively the estimate of the gravity field. Although, variational equations perform better, it is important that both positions and range rates are combined and they are properly weighted in solving normal equations.

Dorsal

Die Luftvorwärmung im Dampfkesselbetriebmissing values and non-uniform sampling as well as observations with varying accuracies. This chapter gives an introduction to DLM and shows how to build various useful models for analysing trends and other sources of variability in geodetic time series.

Arteriography

Arteriography

Book 2020 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 mo

Popcorn

Enzyme

https://doi.org/10.1007/978-3-662-34599-3lso illuminate the diversity of ways in which the Earth moves and deforms. We distinguish between the deterministic approach to trajectory modelling, which emphasizes the physical meaning of the various components of the trajectory, and a more automatic, autonomous and heuristic approach to finding and fitting a trajectory model.

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