Differential Interferometric Synthetic Aperture Radar (DInSAR) based mapping of surface deformation has proven valuable in a variety of geoscience applications. Conventional approaches to DInSAR analysis require significant expertise and are not suited to addressing the opportunities and challenges presented by the large multi-temporal SAR datasets generated by future radar constellations. As a result, the Canada Centre for Mapping and Earth Observation (CCMEO) developed, in support of Natural Resources Canada and Government of Canada priorities, a system for automatic generation of standard and advanced deformation products based on DInSAR technology from RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) data. Existing RADARSAT-2 processing algorithms were adapted to RCM specifications and novel advanced processing algorithms were developed to address the large data sets resulting from the constellation’s four-day rapid revisit cycle. This permitted expanding the DInSAR functionality across a wide-range of spatial and temporal scales. The system architecture is scalable and can be expanded to serve a large number of clients; it can simultaneously address multiple application areas including natural and anthropogenic hazards, natural resource development, permafrost and glacier monitoring, coastal and environmental change and wetlands mapping.

Simple models of fluid and solid mechanics predict that the depressurization of a shallow reservoir that occurs during large effusive eruptions produces exponential trends in time series of both pressure drop and extruded volume. These models are attractive due to their simplicity and because they can explain geodetic and extruded volume data recorded at several volcanoes like at St. Helens and Cordón Caulle, regardless of their magma compositions. However, several lava and dome-forming eruptions like at Redoubt, Hekla and Santiaguito volcanoes do not show clear ground deformation coeval to lava and dome effusion despite the extrusion of at least 0.1 km3 DRE of magma. This apparent paradox can be explained by a variety of factors including deep magma sources and highly compressible magmas that leave no geodetic footprint. Here we explore the role of magma buoyancy with a reanalysis of ALOS-1, TerraSAR-X and RADARSAT-2 InSAR ground deformation and Pleiades DEM data of the VEI 5 Plinian and dome forming rhyolitic eruption of Chaitén volcano in 2008-2009. We show that almost all of the recorded ground deformation occurred during the first three weeks of the eruption, which implies that the extrusion of a rhyolitic dome (~0.8 km3 DRE) did not result in significant depressurization of a magma reservoir, despite the clear exponential trends in the extrusion data. Instead, we show that the exponential trend in the time series of extruded volume can be explained by magma ascending due its buoyancy instead of its overpressure. These results imply that ground deformation alone is not always indicative of the temporal evolution of an eruption and urges for the acquisition of denser time series of DEM data to calculate time-lapse extrusion rates.

The ever-increasing amount of SAR data motivates the development of automatic processing chains to fully exploit the opportunities offered by these large databases. The InSAR Mass processing Toolbox for Multidimensional time series (MasTer) is an optimized tool to automatically download SAR data, select the interferometric pairs, perform the interferometric mass processing, compute the geocoded deformation maps, invert and display the velocity maps and the 2D time series on a web page updated incrementally as soon as a new image is available. New challenges relate to data management and processing load. We address them through methodological improvements dedicated to optimizing the InSAR pair selection. The proposed algorithm narrows the classical selection based on the shortest temporal and spatial baselines thanks to a coherence proxy and balances the use of each image as Primary and Secondary images thanks to graph theory methods. We apply the processing to three volcanic areas characterized with different climate, vegetation and deformation characteristics: the Virunga Volcanic Province (DR Congo), the Reunion Island (France) and the Domuyo and Laguna del Maule area (Chile-Argentina border). Compared to pair selection based solely on baseline criteria, this new tool produces similar velocity maps while reducing the total number of computed differential InSAR interferograms by up to 75\%, which drastically reduces the computation time. The optimization also allows to reduce the influence of DEM errors and atmospheric phase screen, which increase the signal-to-noise ratio of the inverted displacement time series.

On the 22nd of May 2021, although no alarming precursory unrest had been reported, Nyiragongo volcano erupted and lava flows threatened about 1 million of inhabitants living in the cities of Goma (Democratic Republic of Congo) and Giseny (Rwanda). After January 1977 and January 2002, it was the beginning of the third historically known flank eruption of Nyiragongo volcano and the first ever to be recorded by dense measurements both on the ground and from space. In the following days, seismic and geodetic data as well as fracture mapping revealed the gradual southward propagation of a shallow dike from the Nyiragongo edifice underlying below Goma airport on May 23-24, then Goma and Gisenyi city centers on May 25-26 and finally below the northern part of Lake Kivu on May 27. Southward migration of the associated seismic swarm slowed down between May 27 and June 02. Micro seismicity became more diffuse, progressively activating transverse tectonic structures previously identified in the whole Lake Kivu basin. Here we exploit ground based and remote sensing data as well as inversion and physics-based models to fully characterize the dike sized, the dynamics of dike propagation and its arrest against a structural lineament known as the Nyabihu Fault. This work highlights the shallow origin of the dike, the segmented dike propagation controlled by the interaction with pre-existing fracture networks and the incremental crater collapse associated with drainage which led to the disappearance of the world’s largest long-living lava lake on top of Nyiragongo.

The increasing amount of Synthetic Aperture Radar (SAR) satellites orbiting the Earth, their increasing time and space resolution, the variety of wavelengths, polarizations and looking geometries, the shortening of data availability latency and the lengthening of archive databases offer unprecedented opportunities for Earth observation and hazard monitoring. The downside is that it brings new challenges for processing that huge amount of data and for making the results quickly analyzable. To fully benefit from these advances in SAR, it requires efficient data processing infrastructure (optimized for processing speed, storage usage and security), efficient data visualization, and standardization of the final products for easy ingestion by conventional analysis tools. We present here the InSAR Mass processing Toolbox for Multidimensional time series (MasTer), which can combine any type of SAR data to produce unsupervised vertical and horizontal ground deformation time series. MasTer is optimized to automatically download SAR data, select the appropriate interferometric pairs, perform the interferometric mass processing, compute the geocoded deformation maps, invert and display the velocity maps and the 2D time series on a web page updated incrementally as soon as a new image is made available. The incremental architecture allows updating the time series within the shortest time possible (typically a few hours) as soon as a new SAR image is provided. Several steps are self-evaluating to ensure robust and reliable processing. Moreover, recent methodological improvement consists in the computation of a coherence proxy to guide the pair selection optimization balancing the use of each image as primary and secondary image during the differential interferometric (DInSAR) processing. Such a pair selection increases both the processing efficiency and the signal-to-noise ratio of the time series. MasTer also allows the production of time series of coherences or SAR amplitude images, which can be used e.g. for land use monitoring or geomorphological changes detection. The capabilities and performances of MasTer will be illustrated with several examples. Software and manual are available upon request from the authors.