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Article

Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China

1
GNSS Research Center, Wuhan University, Wuhan 430079, China
2
Geodetic Institute, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
3
Institute of Geodesy, University of Stuttgart, 70174 Stuttgart, Germany
4
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong 999077, China
5
IGN LAREG, Université Paris Diderot, Paris 75005, France
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 958; https://doi.org/10.3390/rs10060958
Submission received: 10 May 2018 / Revised: 28 May 2018 / Accepted: 12 June 2018 / Published: 15 June 2018
(This article belongs to the Special Issue Remote Sensing of Tectonic Deformation)

Abstract

Mass redistribution of the atmosphere, oceans, and terrestrial water storage generates crustal displacements which can be predicted by environmental loading models and observed by the Global Positioning System (GPS). In this paper, daily height time series of 235 GPS stations derived from a homogeneously reprocessed Crustal Movement Observation Network of China (CMONOC) and corresponding loading displacements predicted by the Deutsche GeoForschungsZentrum (GFZ) are compared to assess the effects of loading corrections on the nonlinear variations of GPS time series. Results show that the average root mean square (RMS) of vertical displacements due to atmospheric, nontidal oceanic, hydrological, and their combined effects are 3.2, 0.6, 2.7, and 4.0 mm, respectively. Vertical annual signals of loading and GPS are consistent in amplitude but different in phase systematically. The average correlation coefficient between loading and GPS height time series is 0.6. RMS of the GPS height time series are reduced by 20% on average. Moreover, an investigation of 208 CMONOC stations with observing time spans of ~4.6 years shows that environmental loading corrections lead to an overestimation of the GPS velocity uncertainty by about 1.4 times on average. Nevertheless, by using a common mode component filter through principal component analysis, the dilution of velocity precision due to environmental loading corrections can be compensated.
Keywords: Global Positioning System (GPS); Crustal Movement Observation Network of China (CMONOC); time series; loading; Common Mode Component (CMC); Principal Component Analysis (PCA) Global Positioning System (GPS); Crustal Movement Observation Network of China (CMONOC); time series; loading; Common Mode Component (CMC); Principal Component Analysis (PCA)
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MDPI and ACS Style

Yuan, P.; Li, Z.; Jiang, W.; Ma, Y.; Chen, W.; Sneeuw, N. Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China. Remote Sens. 2018, 10, 958. https://doi.org/10.3390/rs10060958

AMA Style

Yuan P, Li Z, Jiang W, Ma Y, Chen W, Sneeuw N. Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China. Remote Sensing. 2018; 10(6):958. https://doi.org/10.3390/rs10060958

Chicago/Turabian Style

Yuan, Peng, Zhao Li, Weiping Jiang, Yifang Ma, Wu Chen, and Nico Sneeuw. 2018. "Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China" Remote Sensing 10, no. 6: 958. https://doi.org/10.3390/rs10060958

APA Style

Yuan, P., Li, Z., Jiang, W., Ma, Y., Chen, W., & Sneeuw, N. (2018). Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China. Remote Sensing, 10(6), 958. https://doi.org/10.3390/rs10060958

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