Crater morphology at active volcanoes can change rapidly. Quantifying changes during the course of a volcanic unrest episode may help assess the level of volcanic activity. However, limitations such as crater accessibility, cloud cover or intra-crater eruptive activity may hamper regular optical or on-site crater monitoring. Here we use multi-sensor satellite Synthetic Aperture Radar (SAR) imagery to produce dense time series of quantitative indicators of crater morphological changes. High temporal resolution is achieved by combining images from a variety of sensors and acquisition modes, though the diversity of acquisition geometries (incidence angle, viewing direction, resolution…) prevents direct comparison between the different images. Using basic trigonometry assumptions, we develop PickCraterSAR, an open-access tool written in Python to measure crater radius and depth from SAR amplitude images in radar geometry. We apply our methodology to study the crater collapse associated with the May 2021 and January 2002 eruptions of Nyiragongo volcano. After the 2021 collapse, we estimate the maximum depth of the crater to be 850 m below the rim and the total volume to be 84$\pm$10 Mm$^3$ (270 m deeper but only 15-20 \% more voluminous than the post-2002 eruption crater). We also show that the 2021 crater collapse occurred progressively while a dike intrusion was migrating toward the south.

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.