Modeling of Residual GNSS Station Motions through Meteorological Data in a Machine Learning Approach

Modeling of Residual GNSS Station Motions through Meteorological Data in a Machine Learning Approach

Long-term Global Navigation Satellite System (GNSS) height residual time series contain signals that are related to environmental influences. A big part of the residuals can be explained by environmental surface loadings, expressed through physical models. This work aims to find a model that connect...

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Bibliographic Details
Main Authors: Pia Ruttner, Roland Hohensinn, Stefano D’Aronco, Jan Dirk Wegner, Benedikt Soja
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Remote Sensing
Subjects:
GNSS
machine learning
environmental loadings
meteorological features
Online Access:https://www.mdpi.com/2072-4292/14/1/17

Internet

https://www.mdpi.com/2072-4292/14/1/17

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