La Palma island is one of the highest potential risks in the volcanic archipelago of the Canaries and therefore it is important to carry out an in-depth study to define its state of unrest. This has been accomplished through the use of satellite radar observations and an original state-of-the-art interpretation technique. Here we show the detection of the onset of volcanic unrest on La Palma island, most likely decades before a potential eruption. We study its current evolution seeing the spatial and temporal changing nature of activity at this potentially dangerous volcano at unprecedented spatial resolutions and long time scales, providing insights into the dynamic nature of the associated volcanic hazard. The geodetic techniques employed here allow tracking of the fluid migration induced by magma injection at depth and identifying the existence of dislocation sources below Cumbre Vieja volcano which could be associated with a future flank failure. Therefore they should continue being monitored using these and other techniques. The results have implications for the monitoring of steep-sided volcanoes at oceanic islands.

La Palma, Canary Islands, underwent volcanic unrest which culminated in its largest historical eruption. We study this unrest along 2021 using Interferometric Synthetic Aperture Radar (InSAR) and a new improved interpretation methodology, comparing achieved results with the crustal structure. We reproduce the final phase of La Palma volcanic unrest, highligthing a shallow magma accumulation which begins about 3.5 months before the eruption in a crustal volume charactherized by low density and fractured rocks. Our modeling, together with our improved pictures of the crustal structure, allows us to explain the location and characteristics of the eruption and to detect failed eruption paths. These can be used to explain post-eruptive phenomena and hazards to the local population, such as detected gases anomalies in La Bombilla and Puerto Naos. Our results have implications for understanding volcanic activity in the Canaries and volcano monitoring elsewhere, helping to support decision-making and providing significant insights into urban and infrastructure planning in volcanic areas.

Differential SAR Interferometry (DInSAR) has proven its unprecedented ability and merits of monitoring ground deformation on a large scale with centimeter to millimeter accuracy. However, atmospheric artifacts due to spatial and temporal variations of the atmospheric state often affect the reliability and accuracy of its results. The commonly-known Atmospheric Phase Screen (APS) appears in the interferograms as ghost fringes not related to either topography or deformation. Atmospheric artifact mitigation remains one of the biggest challenges to be addressed within the DInSAR community. State-of-the-art research works have revealed that atmospheric artifacts can be partially compensated with empirical models, point-wise GPS zenith path delay, and numerical weather prediction models. In this study, we implement an accurate and realistic computing strategy using atmospheric reanalysis ERA5 data to estimate atmospheric artifacts. With this approach, the Line-of-Sight (LOS) path along the satellite trajectory and the monitored points is considered, rather than estimating it from the zenith path delay. Compared with the zenith delay-based method, the key advantage is that it can avoid errors caused by any anisotropic atmospheric phenomena. The accurate method is validated with Sentinel-1 data in three different test sites: Tenerife island (Spain), Almería (Spain), and Crete island (Greece). The effectiveness and performance of the method to remove APS from interferograms is evaluated in the three test sites showing a great improvement with respect to the zenith-based approach.

Mitigating atmospheric phase delay is one of the largest challenges facing the differential synthetic aperture radar interferometry (DInSAR) community. Recently, many publications have studied correcting stratified tropospheric phase delay by assuming a linear model between them and topography. However, most of these studies have not considered the effect of turbulent atmospheric artefacts when adjusting the linear model to data. In this paper, we present an improved technique that minimizes the influence of turbulent atmosphere in the model adjustment. In the proposed algorithm, the model is adjusted to the phase differences of pixels instead of using the unwrapped phase of each pixel. In addition, the different phase differences are weighted as a function of its Atmospheric Phase Screen (APS) covariance estimated from an empirical variogram to reduce in the model adjustment the impact of pixel pairs with significant turbulent atmosphere. The good performance of the proposed method has been validated with both simulated and real Sentinel1-A SAR data in the mountainous area of Tenerife island, Spain. Index Terms-Synthetic aperture radar (SAR), Interferometric SAR (InSAR), APS, modelling.