A Comprehensive Analysis of Environmental Loading Effects on Vertical GPS Time Series in Yunnan, Southwest China

Hu, Shunqiang; Chen, Kejie; Zhu, Hai; Chen, Xue; Wang, Tan; Yang, Zhenyu; Zhao, Qian

doi:10.3390/rs14122741

Cited by 7 publications

(4 citation statements)

References 39 publications

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“…The amplitude of NTOL was found to be greater at stations situated along the coastline than those farther from the coastline. Additionally, the amplitude of HYDL in mainland China was mainly the largest in the southwestern region, which was likely due to the substantial hydrological load generated by the annual monsoon in South and Southeast Asia [22,49]. Moreover, the annual amplitudes of SLMs and GNSS in North and Southwest China significantly differ from those in other regions.…”

Section: Adaptation Of the Slms In Different Areas Of Mainland Chinamentioning

confidence: 99%

Assessing the Nonlinear Changes in Global Navigation Satellite System Vertical Time Series with Environmental Loading in Mainland China

Zhang,

Li,

Zhang

et al. 2023

Remote Sensing

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This study investigated the nonlinear changes in the vertical motion of 411 GNSS reference stations situated in mainland China and assessed the influence of the environmental load on their vertical displacement. The researchers evaluated the effect of environmental load by calculating the change in annual cycle amplitude before and after its removal, focusing on its impact across regions with distinct foundation types. The results demonstrate that removing the environmental load led to a considerable reduction of approximately 50.25% in the annual cycle amplitude of vertical motion for GNSS reference stations in mainland China. This reduction in amplitude improved the positioning accuracy of the stations, with the highest WRMS reduction being 2.72 mm and an average reduction of 1.03 mm. The most significant impact was observed in the southwestern, northern, and northwestern regions, where the amplitude experienced a notable decrease. Conversely, the southeastern region exhibited a corresponding increase in amplitude. This article innovatively explored the effects of environmental loads on diverse foundation types. When categorizing GNSS reference stations based on their foundation type, namely, bedrock, 18 m soil layer, and 4–8 m soil layer stations, this study found that removing the environmental load resulted in reductions in annual cycle amplitudes of 49.37%, 59.61%, and 46.48%, respectively. These findings indicate that 18 m soil layer stations were more susceptible to environmental load-induced vertical motion. In conclusion, the impact of the environmental load was crucial when analyzing the vertical motion of GNSS reference stations in mainland China, as it was essential for establishing a high-precision coordinate reference framework and studying the tectonic structure of the region.

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Section: Adaptation Of the Slms In Different Areas Of Mainland Chinamentioning

confidence: 99%

Assessing the Nonlinear Changes in Global Navigation Satellite System Vertical Time Series with Environmental Loading in Mainland China

Zhang,

Li,

Zhang

et al. 2023

Remote Sensing

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“…It may also be applied to assess how similar the GPS station residual series are to one another. The time series of the common epoch of two stations is used to calculate the correlation coefficient (Hu et al, 2022):…”

Section: The Correlation Of Residual Seriesmentioning

confidence: 99%

Effects of different seasonal fitting methods on the spatial distribution characteristics of common mode errors

et al. 2023

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This study investigated the effects of various seasonal fitting techniques on the spatial distribution of the common mode errors taking the coordinate time series of the continuous GPS reference stations of the Crustal Movement Observation Network of China (CMONOC) as an example. First, the seasonal term of coordinate time series was calculated using constant amplitude harmonic fitting (CAF), continuous wavelet transform (CWT), and smoothing spline fitting (SPF). The seasonal term and linear trend were then removed to obtain the residual time series. Finally, to determine the common mode errors of residual time series, principal component analysis (PCA) was applied. The results indicate that 1) smoothing spline fitting is superior to constant amplitude harmonic fitting and continuous wavelet transform in its ability to fit short-term irregular seasonal signals. In comparison to constant amplitude harmonic fitting, N/E/U has root mean square error (RMSE) values of smoothing spline fitting that are lower by 25%, 20%, and 14.4%, respectively. Smoothing spline fitting also has a higher coefficient of determination than continuous wavelet transform and constant amplitude harmonic fitting. The coefficient of determination in the U direction is larger than that in the N and E directions. 2) Each order PC of the residual series fitted by smoothing spline fitting exhibits apparent spatial aggregation characteristics, with PC1 having a uniform spatial distribution and presenting a largely positive response. Nevertheless, the residual series obtained by constant amplitude harmonic fitting and continuous wavelet transform exhibits scattered spatial response distribution features in each order PC. Compared to N and E, U’s spatial response distribution is distinct. From north to south, the spatial response of PC1 in the U direction progressively diminishes. In addition to being much lower than that in other locations, the Sichuan–Yunnan region’s spatial response value of PC1 and PC3 also exhibits a clear negative reaction. The root mean square error value of the residual series after smoothing spline fitting is the least, and the filtering effect is the best when comparing the spatial filtering effect based on the three fitting methods. We also compared the root mean square error reduction ratio before and after spatial filtering, and the results showed that the root mean square error reduction ratio before and after the residual series obtained by smoothing spline fitting is slightly larger than that obtained by other methods.

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“…that are contaminated by various types of noise (i.e., stochastic processes and correlations). Several papers have contributed to GNSS and its application to crustal deformation and geodynamics [63][64][65][66][67]; civil engineering [68,69]; stochastic noise modelling [70,71]; natural hazards such as landslides [36,37,72]; SLR estimation and coastal flooding [73][74][75]; hydrology, seasonal displacements, and drought monitoring using GNSS and/or GRACE/GRACE-FO [76][77][78]; and the study of ionospheric disturbances [79][80][81], together with research focused on the stability of the reference frame [82].…”

Section: Concluding Remarks On Contributions Of the Special Issue Of ...mentioning

confidence: 99%

Recent Advances in Modelling Geodetic Time Series and Applications for Earth Science and Environmental Monitoring

Montillet

Zhao

et al. 2022

Remote Sensing

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Geodesy is the science of accurately measuring the topography of the earth (geometric shape and size), its orientation in space, and its gravity field. With the advances in our knowledge and technology, this scientific field has extended to the understanding of geodynamical phenomena such as crustal motion, tides, and polar motion. This Special Issue is dedicated to the recent advances in modelling geodetic time series recorded using various instruments. Due to the stochastic noise properties inherent in each of the time series, careful modelling is necessary in order to extract accurate geophysical information with realistic associated uncertainties (statistically sufficient). The analyzed data have been recorded with various space missions or ground-based instruments. It is impossible to be comprehensive in the vast and dynamic field that is Geodesy, particularly so-called “Environmental Geodesy”, which intends to understand the Earth’s geodynamics by monitoring any changes in our environment. This field has gained much attention in the past two decades due to the need by the international community to understand how climate change modifies our environment. Therefore, this Special Issue collects some articles which emphasize the recent development of specific algorithms or methodologies to study particular natural phenomena related to the geodynamics of the earth’s crust and climate change.

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A Comprehensive Analysis of Environmental Loading Effects on Vertical GPS Time Series in Yunnan, Southwest China

Cited by 7 publications

References 39 publications

Assessing the Nonlinear Changes in Global Navigation Satellite System Vertical Time Series with Environmental Loading in Mainland China

Assessing the Nonlinear Changes in Global Navigation Satellite System Vertical Time Series with Environmental Loading in Mainland China

Effects of different seasonal fitting methods on the spatial distribution characteristics of common mode errors

Recent Advances in Modelling Geodetic Time Series and Applications for Earth Science and Environmental Monitoring

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