Chapter 1 Introduction 1.1 Scientific background 1.1.1 GPS solution approaches 1.1.2 Strong-motion data solution approaches 1.1.3 Integration of GPS and accelerometer observations 1.2 Aims and objectives 1.2.1 Augmentation approach 1.2.2 Integration approach 1.2.3 Adaptive approach 1.2.4 The key issues about integration 1.2.5 The relationship between baseline shift and ground tiling 1.3 Organization of the book Chapter 2 Real-time monitoring the ground motion using GPS with real time corrections 2.1 Introduction 2.2 Methodology 2.2.1 The velocity determination model based on broadcast ephemeris 2.2.2 Extracting corrections from the reference station 2.2.3 The velocity determination model based on reference station correction 2.2.4 Retrieve the final true velocity and displacement 2.2.5 The data processing flow of the augmentation approach 2.3 Experiment analysis 2.3.1 Comparison of displacement and velocity between GPS and strong-motion sensor 2.3.2 Comparison of displacement and velocity results between different sample rate data 2.3.3 Comparison of GPS results between the single station method and augmentation method 2.3.4 Comparison of the observation residuals and initial trend drift correction 2.4 Conclusion Chapter 3 Application of a net-based baseline correction scheme to strong-motion records of the 2011 Mw 9.0 Tohoku earthquake 3.1 Introduction 3.2 Methodology 3.2.1 Selection of reference records 3.2.2 Net-based correction on target records 3.2.3 Detection of outlier records 3.3 Application to strong-motion data for the 2011 Mw 9.0 Tohoku earthquake 3.3.1 Data 3.3.2 Selected reference records 3.3.3 Augmented target records 3.3.4 Outlier records 3.3.5 Improvements over the previous empirical approaches 3.4 Conclusion and discussion Chapter 4 Cost-effective monitoring of ground motion related to earthquakes, landslides or volcanic activity by joint use of a single-frequency GPS and a MEMS accelerometer 4.1 Introduction 4.2 Method 4.3 Outdoor experiments 4.4 Discussion and conclusions Chapter 5 A new algorithm for tight integration of real-time GPS and strong-motion records, demonstrated on simulated, experimental and real seismic data 5.1 Introduction 5.2 Mathematical model 5.3 A new approach to combine GPS and seismic accelerometer data 5.4 Validation and analysis 5.4.1 Simulated dataset 5.4.2 Experimental Test 5.4.3 Application to a real earthquake : E1 Mayor-Cucapah Mw 7.2, 2010 5.5 Summary and discussion Chapter 6 Adaptive recognition and correction of baseline shifts from collocated GPS and accelerometer using two phases Kalman filter 6.1 Introduction 6.2 Methodology 6.2.1 The model for tight integration of GPS and strong-motion measurements 6.2.2 The adaptive recognition of baseline shifts in strong-motion records 6.2.3 The implementation process 6.3 Validation 6.3.1 Experimental test using a shaking table 6.3.2 Application to a real earthquake:2011 Mw 9.0 Tohoku earthquake 6.4 Conclusion Chapter 7 An improved loose integration method of coseismie waves retrieving from collocated GPS and accelerometer 7.1 Introduction 7.2 Overview of the traditional loose integration method 7.3 The improved loose integration method 7.4 Validation and analysis 7.5 Conclusion Chapter 8 An improved method for tight integration of GPS and strong-motion records: complementary advantages 8.1 Introduction 8.2 Methodology 8.2.1 Using GPS to estimate baseline shifts for the strong-motion sensor 8.2.2 Using acceleration to constrain GPS solution and ambiguity-resolution 8.2.3 The implementation process of the method 8.3 Validations 8.3.1 Analysis of the baseline shift 8.3.2 Analysis of the displacement time series 8.3.3 Analysis of the zenith tropospheric delay 8.3.4 Analysis of the waveforms 8.4 Conclusions and discussions Chapter 9 The study of key issues about integration of GNSS and strong-motion records for real-time earthquake monitoring 9.1 Introduction 9.2 Method and Data 9.3 Validation and analysis 9.3.1 Coordinate system 9.3.2 GNSS sampling rate 9.3.3 The constrain of the dynamic noises 9.3.4 GNSS data quality 9.3.5 Convergence speed 9.3.6 Ambiguity resolution 9.4 Conclusions and discussions Chapter 10 The study of baseline shift error in strong-motion and ground tilting during co-seismic period based on GPS observations 10.1 Introduction 10.2 Extracting strong-motion baseline shift based on GPS observation 10.3 Extracting of ground tilting information based on GPS observation 10.4 Validation and analysis 10.4.1 Experiment introduction and data processing 10.4.2 Result analysis 10.4.3 A case study of the earthquake event: 2011 Mw 9.0 Tohoku-Oki earthquake 10.5 Conclusion Chapter 11 Comparison of high-rate GPS, strong-motion records and their joint use for earthquake monitoring: a ease study of the 2011 nw 9.0 Tohoku earthquake 11.1 Introduction 11.2 Datasets and processing approaches 11.2.1 Data description 11.2.2 Processing approaches 11.3 Results and analysis 11.3.1 Comparison of horizontal co-seismic movement 11.3.2 Comparison in time-frequency domain of the displacement time series 11.3.3 Comparison of velocity waveforms 11.3.4 Comparison of P wave detection 11.4 Conclusions and discussions Chapter 12 Synthesis 12.1 Conclusions 12.1.1 GPS velocity estimation augmentation approach 12.1.2 Strong-motion net-based augmentation approach 12.1.3 Loose integration of GPS and strong-motion observations 12.1.4 Tight integration of GPS and strong-motion observations 12.1.5 Adaptive integration of GPS and strong-motion observations 12.1.6 Improved loose integration of GPS and strong-motion observations 12.1.7 Improved tight integration of GPS and strong-motion observations 12.1.8 Key issues of integration of GPS and strong-motion observations 12.1.9 Relationship between baseline shifts and ground tilting 12.1.10 Comparison of different sensors for earthquake monitoring and early warning 12.2 Outlook 12.2.1 Study the earthquake early warning model 12.2.2 Study the integration of multi-sensor and data quality control 12.2.3 Develop a new sensor and real-time application system Acronyms and abbreviations References