Three techniques for extracting small signals from kinematic GNSS time series are reviewed. The first is the empirical orthogonal function, which the author used to extract coseismic/postseismic displacements observed immediately after the 2011 off the Pacific coast earthquake. The second is the time-dependent inversion of a time-variable scaling factor, which the author used to evaluate thermal deformations of the GNSS monuments using tilt-meters and kinematic GNSS time series. The third is the stacking method, which the author used to extract displacements associated with tilt-change/very long period seismic signal ( TC/VLP) events observed during the earlystage of 2000 Miyake-jima volcanic crisis. Furthermore, a prototype system for estimating kinematic GNSS time series of Japanese GEONET stations to make kinematic GNSS time series easily accessible is summarized.
The Geospatial Information Authority of Japan (GSI) has carried out nationwide gravity measurements covering the whole of Japan for about 60 years and provided a nationwide gravity standard network. It has been widely used for various purposes such as calculation of orthometric heights, calibration of weighing instruments and exploration of underground structure. However, modernization of the gravity standard network is required because of gravity changes caused by crustal deformation and it has become possible to be realized thanks to recent improvements of gravimeters. Therefore GSI released the modernized new gravity network, named the Japan Gravity Standardization Net 2016 (JGSN2016), on 15 March 2017 for the first time in 40 years.
JGSN2016 consists of gravity values at 32 fundamental gravity points and 231 primary gravity points. Each gravity value was calculated by following steps; 1) determining absolute gravity value of each fundamental gravity point based on absolute gravity measurements, 2) measuring gravitational differences along each baseline by relative gravity measurements and 3) calculating the most probable values of each primary gravity point by carrying out network adjustment with fixing the values of 1). In the course of the above procedures, we corrected for the influences of solid earth tide, atmospheric pressure, polar motion and ocean tide after removing outliers by statistical screening. In addition, the most appropriate combination of parameters for the network adjustment was determined by using the Bayesian Information Criterion (BIC). The absolute gravimeters were calibrated through comparison with the one owned by the National Institute of Advanced Industrial Science and Technology (AIST) who periodically joins in the recent International Comparison of Absolute Gravimeters (ICAG). Thanks to all these kinds of improvements, JGSN2016 achieves 3.0 μGal and 11 μGal precision for the fundamental and primary gravity points, respectively.
The final products of JGSN2016 are freely provided from GSIʼs website (https://sokuseikagis1.gsi.go.jp/top.html) and all data of the absolute gravity measurements are registered to the Absolute Gravity Database (AGrav) with expecting to contribute to activities of Global Geodetic Observing System (GGOS). This paper reviews the details of JGSN2016 construction with briefly touching the history and significance of GSIʼs gravity measurements.
We applied InSAR time series analysis using ALOS-2 data (September 2014 to October 2017) to the Kirishima volcano group, and successfully detected localized and slow ground surface displacement around Mt. Shinmoe and Mt. Iwo. Mt Shinmoe had slowly inflated for two years or more, and it can be explained well by reaccumulation of magma at a shallow source beneath the crater which was estimated to have deflated between November 2011 and May 2013. Such localized and slow displacement is difficult to be detected by other methods than InSAR time series analysis. We also investigated the effect of atmospheric noise reduction using a numerical weather model. The numerical weather model significantly mitigated a stratification component of the atmospheric noise, which has a seasonal and topographical correlation. Without the numerical weather model, the seasonal atmospheric noise may leak into the time series of displacement, even if a spatio-temporal filter is applied, possibly resulting in an incorrect assessment of volcanic activities.
Rapid understanding of the magnitude of large earthquakes in the offshore region and their associated fault expansions is important for near-field tsunami forecasting. Since September 2012, the Geospatial Information Authority of Japan (GSI) and Tohoku University have been jointly developing the GEONET real-time analysis system (REGARD), which is expected to provide reliable earthquake magnitude estimation. The REGARD system has two different types of coseismic fault model estimation systems. The first system estimates the slip distribution along the plate boundary, while the second comprises single rectangular fault model estimation. One of the challenges of REGARD is the difficulty in the estimation of the quantitative uncertainty in the single rectangular fault estimation. Thus, we focused on quantitatively understanding the single rectangular fault model estimation based on real-time GNSS time series data. We adopted Markov Chain Monte Carlo methods (MCMC) for modeling of the coseismic single fault. We applied the Metropolis–Hastings MCMC method to the 2011 Tohoku-Oki earthquake. The results obtained clearly demonstrated the tradeoff between the fault area and the amount of slip. The posterior probability density function (PDF) of the obtained slip amount showed a complex shape compared with those for the other unknown parameters. Thus, we focused on the stress drop value. Based on multiple Markov chains using Gaussian prior PDF for the stress drop with different mean value (5, 10, 15, 20, and 25 MPa), we successfully obtained the simple posterior PDF shape of the slip amount for each different mean value condition. We also found that the entire fault model explained the data well. These results suggest that the data cannot resolve uncertainties from the tradeoff between the fault area and the slip amount, which are extremely important factors for precise near-field tsunami forecasting. The results obtained using different constraint condition for the stress drop by prior distribution may provide the quantitative uncertainties for the resulting tsunamis.
Water vapor molecules from ascending missiles or rockets often cause ionospheric electron depletion, which could be detected as changes in total electron content (TEC) by ground GNSS receivers. Here we present six cases of North Korean missiles/rockets launched in 1998-2017, and compare them with three examples of H2A launches from Japan. We found that the TEC drops are proportional to the background TEC for the same type of rockets, and classified the past cases into three groups using the ratios of TEC drops to the original TEC, i.e. the H2A class, the Taepodong-2 class, and the Taepodon-1 class. Missiles or rockets from North Korea 2009-2016 all belonged to the Taepodong-2 class. In 2017, two inter-continental ballistic missiles (ICBM) were launched from North Korea in July and in November. The first one showed ionospheric electron depletion comparable to the Taepodon-2 class cases, but the second missile much larger TEC drops possibly reflecting a significant technological progress within 2017.
Sentinel-1 satellites equipped with C-band synthetic aperture radar are providing invaluable data on the Earth’s surface since the launch of the first satellite in April 2014. Owing to the wide swath of radar and short recurrence interval, researches of crustal deformations associated with earthquake and volcanic eruptions, landslide, land subsidence, etc. have been made in several regions on the Earth. Especially, stable observation with the same configuration enables us to reveal temporal evolution of surface deformations using sophisticated time series analysis. Furthermore, all data are freely available to scientific community, which boosts researches in various fields. So far, however, there are not many studies utilizing Sentinel-1 images in the Japanese community of crustal deformation study. This may be partly because shorter wavelength microwave SAR is inferior to L-band SAR in heavily vegetated area such as Japan, and partly because special techniques are required to process images. In this article I present the overview of the system of Sentinel-1 and its merit and demerit, processing examples and finally give perspectives on research with SAR.
Laboratory experiments of radar measurement were conducted with the aim of confirming the effect of vegetation on surface deformation detection using InSAR. Rotating vegetation was set between radar antennas and a corner reflector, and attenuation and phase variation of radar microwave through vegetation were investigated. This experiment was performed at three different frequency bands: Ku-, X-, and L-band. We confirmed larger attenuation in higher radar frequency and better penetration with horizontal polarization. Generally, the more densely developed in its branches and leaves of vegetation, the larger attenuation was observed with a few exceptions; it may depend on radar type ( polarization and wavelength ) and shape of vegetation. In the case that backscatter from vegetation is dominant, large phase change was detected and furthermore it could slightly affect phase at pixel behind vegetation. Investigating phase and amplitude dispersions of interferogram, obvious relation of them was confirmed and frequency dependency about it was not detected.