One of the limitations of deformation measurements made with interferometric synthetic aperture radar (InSAR) is that an interferogram only measures one component of the surface deformation — in the satellite's line of sight. We investigate strategies for mapping surface deformation in three dimensions by using multiple interferograms, with different imaging geometries. Geometries for both current and future missions are evaluated, and their abilities to resolve the displacement vector are compared. The north component is always the most difficult to determine using data from near‐polar orbiting satellites. However, a satellite with an inclination of about 60°/120° would enable all three components to be well resolved. We attempt to resolve the 3D displacements for the 23 October 2002 Nenana Mountain (Alaska) Earthquake. The north component's error is much larger than the signal, but proxies for eastward and vertical motion can be determined if the north component is assumed negligible. Inversions of hypothetical coseismic interferograms demonstrate that earthquake model parameters can be well recovered from two interferograms, acquired on ascending and descending tracks.

An earthquake with a dozen faults: The 2016 moment magnitude ( M _w ) 7.8 Kaikōura earthquake was one of the largest ever to hit New Zealand. Hamling et al. show with a new slip model that it was an incredibly complex event. Unlike most earthquakes, multiple faults ruptured to generate the ground shaking. A remarkable 12 faults ruptured overall, with the rupture jumping between faults located up to 15 km away from each other. The earthquake should motivate rethinking of certain seismic hazard models, which do not presently allow for this unusual complex rupture pattern. Science , this issue p. eaam7194

Correcting for tropospheric delays is one of the largest challenges facing the interferometric synthetic aperture radar (InSAR) community. Spatial and temporal variations in temperature, pressure, and relative humidity create tropospheric signals in InSAR data, masking smaller surface displacements due to tectonic or volcanic deformation. Correction methods using weather model data, GNSS and/or spectrometer data have been applied in the past, but are often limited by the spatial and temporal resolution of the auxiliary data. Alternatively a correction can be estimated from the interferometric phase by assuming a linear or a power-law relationship between the phase and topography. Typically the challenge lies in separating deformation from tropospheric phase signals. In this study we performed a statistical comparison of the state-of-the-art tropospheric corrections estimated from the MERIS and MODIS spectrometers, a low and high spatial-resolution weather model (ERA-I and WRF), and both the conventional linear and new power-law empirical methods. Our test-regions include Southern Mexico, Italy, and El Hierro. We find spectrometers give the largest reduction in tropospheric signal, but are limited to cloud-free and daylight acquisitions. We find a ~10–20% RMSE increase with increasing cloud cover consistent across methods. None of the other tropospheric correction methods consistently reduced tropospheric signals over different regions and times. We have released a new software package called TRAIN (Toolbox for Reducing Atmospheric InSAR Noise), which includes all these state-of-the-art correction methods. We recommend future developments should aim towards combining the different correction methods in an optimal manner

For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (~km) relative displacements with an accuracy of <1 cm/epoch and ~2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.