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.

Space-borne Synthetic Aperture Radar (SAR) Interferometry (InSAR) is now a key geophysical tool for surface deformation studies. The European Commission’s Sentinel-1 Constellation began acquiring data systematically in late 2014. The data, which are free and open access, have global coverage at moderate resolution with a 6 or 12-day revisit, enabling researchers to investigate large-scale surface deformation systematically through time. However, full exploitation of the potential of Sentinel-1 requires specific processing approaches as well as the efficient use of modern computing and data storage facilities. Here we present Looking Into Continents from Space with Synthetic Aperture Radar (LiCSAR), an operational system built for large-scale interferometric processing of Sentinel-1 data. LiCSAR is designed to automatically produce geocoded wrapped and unwrapped interferograms and coherence estimates, for large regions, at 0.001° resolution (WGS-84 coordinate system). The products are continuously updated at a frequency depending on prioritised regions (monthly, weekly or live update strategy). The products are open and freely accessible and downloadable through an online portal. We describe the algorithms, processing, and storage solutions implemented in LiCSAR, and show several case studies that use LiCSAR products to measure tectonic and volcanic deformation. We aim to accelerate the uptake of InSAR data by researchers as well as non-expert users by mass producing interferograms and derived products.

Measurements of present‐day surface deformation are essential for the assessment of long‐term seismic hazard. The European Space Agency's Sentinel‐1 satellites enable global, high‐resolution observation of crustal motion from Interferometric Synthetic Aperture Radar (InSAR). We have developed automated InSAR processing systems that exploit the first ~5 years of Sentinel‐1 data to measure surface motions for the ~800,000‐km² Anatolian region. Our new 3‐D velocity and strain rate fields illuminate deformation patterns dominated by westward motion of Anatolia relative to Eurasia, localized strain accumulation along the North and East Anatolian Faults, and rapid vertical signals associated with anthropogenic activities and to a lesser extent extension across the grabens of western Anatolia. We show that automatically processed Sentinel‐1 InSAR data can characterize details of the velocity and strain rate fields with high resolution and accuracy over large regions. These results are important for assessing the relationship between strain accumulation and release in earthquakes.

We constructed and analyzed the ground surface displacement associated with the 2016 Kumamoto earthquake sequence using satellite radar interferometry images of the Advanced Land Observing Satellite 2. The radar interferogram generally shows elastic deformation caused by the main earthquakes, but many other linear discontinuities showing displacement are also found. Approximately 230 lineaments are identified, some of which coincide with the positions of known active faults, such as the main earthquake faults belonging to the Futagawa and Hinagu fault zones and other minor faults; however, there are much fewer known active faults than lineaments. In each area, the lineaments have a similar direction and displacement to each other; therefore, they can be divided into several groups based on location and major features. Since the direction of the lineaments coincides with that of known active faults or their conjugate faults, the cause of the lineaments must be related to the tectonic stress field of this region. The lineaments are classified into the following two categories: (1) main earthquake faults and their branched subfaults and (2) secondary faults that are not directly related to the main earthquake but whose slip was probably triggered by the main earthquake or aftershocks. Graphical Abstract Identified linear surface ruptures. Small solid lines show identified linear surface ruptures. Long, narrow orange area shows the InSAR decorrelation zone along the Futagawa fault zone. Small circles and triangles show epicenters from April 14 to April 23, and beach ball diagrams are from JMA (2016a, b). Red lines show surface ruptures identified by field survey (Geological Survey of Japan 2016).

Temporal decorrelation is one of the main limitations of synthetic aperture radar (SAR) interferometry. For nonurban areas, its mechanism is very complex, as it is very dependent of vegetation types and their temporal dynamics, actual land use, soil types, and climatological circumstances. Yet, an a priori assessment and comprehension of the expected coherence levels of interferograms are required for designing new satellite missions (in terms of frequency, resolution, and repeat orbits), for choosing the optimal data sets for a specific application, and for feasibility studies for new interferometric applications. Although generic models for temporal decorrelation have been proposed, their parameters depend heavily on the land use in the area of interest. Here, we report the behavior of temporal decorrelation for a specific class of land use: pasture on drained peat soils. We use L-, C-, and X-band SAR observations from the Advanced Land Observation Satellite (ALOS), European Remote Sensing Satellite, Envisat, RADARSAT-2, and TerraSAR-X missions. We present a dedicated temporal decorrelation model using three parameters and demonstrate how coherent information can be retrieved as a function of frequency, repeat intervals, and coherence estimation window sizes. New satellites such as Sentinel-1 and ALOS-2, with shorter repeat intervals than their predecessors, would enhance the possibility to obtain a coherent signal over pasture.

Ground subsidence in urban areas is a significant problem because it increases flood risk, damages buildings and infrastructure, and results in economic loss. Continual monitoring of ground deformation is important for early detection, mechanism understanding, countermeasure implementation, and deformation prediction. The Sentinel-1 satellite constellation has globally and freely provided frequent and abundant SAR data and enabled nationwide deformation monitoring through InSAR time series analysis. LiCSAR, an automatic Sentinel-1 interferometric processing system, has produced abundant interferograms with global coverage, and the products are freely accessible and downloadable through a web portal. LiCSBAS, an open source InSAR time series analysis package integrated with LiCSAR, enables users to obtain the deformation time series easily and quickly. In this study, spatially and temporally detailed deformation time series and velocities from the LiCSAR products using LiCSBAS for 73 major urban areas in Japan during 2014–2020 were derived. All LiCSBAS processing was automatically performed using predefined parameters. Many deformation signals with various temporal and spatial features, such as linear subsidence in Hirosaki, Kujyukuri, Niigata, and Kanazawa, episodic subsidence in Sanjo, annual vertical fluctuation in Hirosaki, Yamagata, Yonezawa, Ojiya, and Nogi, and linear uplift in Chofu were detected. Unknown small nonlinear uplift signals were found in Nara and Osaka in 2018. Complex postseismic deformations from the 2016 Kumamoto earthquake were also revealed. All the deformation data obtained in this study are available on an open repository and are expected to be used for further research, investigation, or interpretation. This nationwide monitoring approach using the LiCSAR products and LiCSBAS is easy to implement and applicable to other areas worldwide.