GPS has been widely used in the field of geodesy and geodynamics thanks to its technology development and the improvement of positioning accuracy. A time series observed by GPS in vertical direction usually contains tectonic signals, non-tectonic signals, residual atmospheric delay, measurement noise, etc. Analyzing these information is the basis of crustal deformation research. Furthermore, analyzing the GPS time series and extracting the non-tectonic information are helpful to study the effect of various geophysical events. Principal component analysis (PCA) is an effective tool for spatiotemporal filtering and GPS time series analysis. But as it is unable to extract statistically independent components, PCA is unfavorable for achieving the implicit information in time series. Independent component analysis (ICA) is a statistical method of blind source separation (BSS) and can separate original signals from mixed observations. In this paper, ICA is used as a spatiotemporal filtering method to analyze the spatial and temporal features of vertical GPS coordinate time series in the UK and Sichuan-Yunnan region in China. Meanwhile, the contributions from atmospheric and soil moisture mass loading are evaluated. The analysis of the relevance between the independent components and mass loading with their spatial distribution shows that the signals extracted by ICA have a strong correlation with the non-tectonic deformation, indicating that ICA has a better performance in spatiotemporal analysis.

Results of inspecting an impact damaged carbon fibre composite specimen are reported. Several physical test procedures and processing .algorithms have been analysed within the framework of the international Round Robin Test. A statistical means for rating non-destructive testing techniques is proposed to convert otiginal infrared images to defect maps that are of special interest for end-users. The :potentials of the techniques for oharacterising shape and depth distribution of impact damage in carbon fibre composites are discussed, 'including comparison with ultrasonic C-scan results.

Ocean tide loading (OTL) causes crustal displacements in coastal regions, and the relative variation of these ground displacements may reach several centimeters across differential interferometric synthetic aperture radar (DInSAR) interferograms. However, orbit errors seriously affect the analysis of long-wavelength crustal deformation signals such as the OTL effect because of their similar signatures in DInSAR interferograms. To correct the orbit errors, we used a linear surface model to model the relative displacements of the Global Positioning System (GPS) precise point positioning (PPP) in the line of sight (LOS) direction as a priori parameter of the long-wavelength crustal deformation signals. After correcting the orbit errors, an ocean tide model was applied to correct the OTL effect in the DInSAR interferograms. The proposed approach was verified with the DInSAR interferograms from the Los Angeles basin. The experimental results confirm that the real orbit errors can be modeled by the bilinear ramp function under the constraint of the priori parameter. Moreover, after removing the orbit errors, the OTL effect, which is dominant in the long-wavelength crustal deformation signals, can be revealed, and then be effectively eliminated by the FES2004 tide model.

Global Positioning System (GPS) kinematic precise point positioning (KPPP) is an effective approach for estimating the Earth’s tidal deformation. The accuracy of KPPP is usually evaluated by comparing results with tidal models. However, because of the uncertainties of the tidal models, the accuracy of KPPP-estimated tidal displacement is difficult to accurately determine. In this paper, systematic vector differences between GPS estimates and tidal models were estimated by least squares methods in complex domain to analyze the uncertainties of tidal models and determine the accuracy of KPPP-estimated tidal displacements. Through the use of GPS data for 12 GPS reference stations in Hong Kong from 2008 to 2017, vertical ocean tide loading displacements (after removing the body tide effect) for eight semidiurnal and diurnal tidal constituents were obtained by GPS KPPP. By an in-depth analysis of the systematic and residual differences between the GPS estimates and nine tidal models, we demonstrate that the uncertainty of the tidal displacement determined by GPS KPPP for the M2, N2, O1, and Q1 tidal constituents is 0.2 mm, and for the S2 constituent it is 0.5 mm, while the accuracy of the GPS-estimated K1, P1, and K2 tidal constituents is weak because these three tidal constituents are affected by significant common-mode errors. These results suggest that GPS KPPP can be used to precisely constrain the Earth’s vertical tidal displacement in the M2, N2, O1, and Q1 tidal frequencies.

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The long-term spatial-temporal deformation monitoring of densely distributed infrastructures near the lake area is of great significance to understand the urban health status and prevent the potential traffic safety problems. In this paper, the permanent scatterer interferometry (PSI) technology with TerraSAR-X imagery over the area around Dongting Lake was utilized to generate the long-term spatial-temporal deformation. Since the X-band SAR interferometric phases are highly influenced by the thermal dilation of the observed objects, and the deformation of large infrastructures are highly related to external temperature, a combined deformation model considering the thermal expansion and the seasonal environmental factors was proposed to model the temporal variations of the deformation. The time series deformation and the thermal dilation parameter over the area were obtained, and a comparative study with the traditional linear model was conducted. The Dongting Lake Bridge and the typical feature points distributed around the lake were analyzed in details. In order to compensate for the unavailability of external in situ measurements over the area, phase residuals and the subsidence generated through Differential Interferometric Synthetic Aperture Radar (D-InSAR) were utilized to verify the accuracy of the obtained deformation time series. Experiment results suggested that the proposed model is suitable and suggested for the selected study site. The root mean square error (RMSE) of the residual phase was estimated as 0.32 rad, and the RMSE compared with D-InSAR derived deformation was ±1.1 mm.

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