![]() IS 3.4: Preliminary guidelines for using the IASPEI standard magnitude reference data set (P. Dewey and IASPEI/CoSOI Working Group on Magnitude Measurement) IS 3.3: The new IASPEI standards for determining magnitudes from digital data and their relation to classical magnitudes (P. IS 3.2: Proposal for unique magnitude and amplitude nomenclature (P. IS 3.1: Theoretical source representation (H. IS 2.1: The IASPEI standard nomenclature of seismic phases (P. IS 1.1: Animations as educational complements to NMSOP-2 (P. ![]() Wendt)ĮX 11.3: Identification and analysis of short-period core phases (tutorial with exercise by hand)(S. Wendt)ĮX 11.2: Earthquake location at teleseismic distances by hand from 3-component records (tutorial with exercise by hand) (P. Wielandt)ĮX 11.1: Estimating the epicenters of local and regional seismic sources by hand, using the circle and chord method (tutorial with exercise by hand and movies) (P. Wielandt)ĮX 5.6: The response of a WWSSN-LP seismograph (E. Wielandt)ĮX 5.5: Interpreting Poles and Zeros from SEED headers (E. Teupser)ĮX 5.4: Seismometer calibration with program CALEX (E. Bribach)ĮX 5.3: Seismometer calibration by harmonic drive (J. Bribach)ĮX 5.2: Estimating seismometer parameters by step function (STEP) (J. Wielandt)ĮX 5.1: Plotting seismograph response (BODE-diagram) (J. Heimann)ĮX 4.1: Bandwidth-dependent transformation of noise data from frequency into time domain and vice versa (P. Bock)ĮX 3.6: A practical on moment tensor inversion using the Kiwi tools (S. Bormann)ĮX 3.5: Moment-tensor determination and decomposition (F. ![]() Bormann)ĮX 3.4: Determination of source parameters from seismic spectra (M. Wendt)ĮX 3.3: Take-off angle calculations for fault plane solutions and reconstruction of nodal planes from the parameters of fault-plane solutions (P. Bormann)ĮX 3.2: Determination of fault plane solutions (P. Diehl)ĮX 3.1: Magnitude determinations (P. Starovoit)ĬHAPTER 16: Automated Event and Phase Identification (L. Parolai)ĬHAPTER 15: CTBTO: Goal, Networks, Data Analysis and Data Availability (J. Wassermann)ĬHAPTER 14: Investigation of Site Response in Urban Areas by using Earthquake Data and Seismic Noise (S. Wendt)ĬHAPTER 12: Intensity and Intensity Scales (R. Bormann)ĬHAPTER 11: Data Analysis and Seismogram Interpretation (P. Kvaerna)ĬHAPTER 10: Seismic Data Formats, Archival and Exchange (B. Asch)ĬHAPTER 7: Site Selection, Preparation and Installation of Seismic Stations (A. Wielandt)ĬHAPTER 6: Seismic Data Acquisition Systems (G. Wielandt)ĬHAPTER 5: Seismic Sensors and their Calibration (E. DiGiacomo)ĬHAPTER 4: Seismic Signals and Noise (P. Kind)ĬHAPTER 3: Seismic Sources and Source Parameters (P. Bormann)ĬHAPTER 2: Seismic Wave Propagation and Earth Models (P. Stratigraphische Tabelle von DeutschlandĬHAPTER 1: History, Aim and Scope of the 1st and 2nd Edition of the IASPEI New Manual of Seismological Observatory Practice (P.New Manual of Seismological Observatory Practice (NMSOP-2) (current).Finally, methods for combining both types of ground‐motion observation systems are discussed, and the wide applicability of this approach is highlighted. Furthermore, a dozen nearby GPS and strong‐motion station pairs are selected to demonstrate that the information in their time series agrees with each other. Comparisons with the corresponding GPS‐based solutions yield a quantitative estimation of uncertainties of the empirical baseline correction. The static coseismic displacement data are obtained by double integration and then used to derive the permanent slip distribution on the earthquake fault. First the strong‐motion records from the two Japanese networks, K‐NET and KiK‐Net, are analyzed using an automatic empirical baseline correction tool. This paper presents a case study on the 2011 M w 9.0 Tohoku earthquake, showing how the ground‐motion information from geodetic and seismic instrumentations is complementary, and suggesting the joint use of both types of data, particularly when the network coverage is sparse. ![]() These wide applications require the ground‐motion data to cover a very broad frequency band that, however, is usually not available. Near‐field ground‐motion data are available in semi‐real time either from modern strong‐motion or continuous Global Positioning System (GPS) networks, allowing robust solutions for earthquake source parameters, which are useful for rapid disaster assessment and early warning. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |