[1] We present here a new InSAR persistent scatterer (PS) method for analyzing episodic crustal deformation in non-urban environments, with application to volcanic settings. Our method for identifying PS pixels in a series of interferograms is based primarily on phase characteristics and finds low-amplitude pixels with phase stability that are not identified by the existing amplitude-based algorithm. Our method also uses the spatial correlation of the phases rather than a well-defined phase history so that we can observe temporally-variable processes, e.g., volcanic deformation. The algorithm involves removing the residual topographic component of flattened interferogram phase for each PS, then unwrapping the PS phases both spatially and temporally. Our method finds scatterers with stable phase characteristics independent of amplitudes associated with man-made objects, and is applicable to areas where conventional InSAR fails due to complete decorrelation of the majority of scatterers, yet a few stable scatterers are present.

Synthetic aperture radar (SAR) interferometry is a technique that provides high‐resolution measurements of the ground displacement associated with many geophysical processes. Advanced techniques involving the simultaneous processing of multiple SAR acquisitions in time increase the number of locations where a deformation signal can be extracted and reduce associated error. Currently there are two broad categories of algorithms for processing multiple acquisitions, persistent scatterer and small baseline methods, which are optimized for different models of scattering. However, the scattering characteristics of real terrains usually lay between these two end‐member models. I present here a new method that combines both approaches, to extract the deformation signal at more points and with higher overall signal‐to‐noise ratio than can either approach alone. I apply the combined method to data acquired over Eyjafjallajökull volcano in Iceland, and detect time‐varying ground displacements associated with two intrusion events.

[1] While conventional interferometric synthetic aperture radar (InSAR) is a very effective technique for measuring crustal deformation, almost any interferogram includes large areas where the signals decorrelate and no measurement is possible. Persistent scatterer (PS) InSAR overcomes the decorrelation problem by identifying resolution elements whose echo is dominated by a single scatterer in a series of interferograms. Existing PS methods have been very successful in analysis of urban areas, where stable angular structures produce efficient reflectors that dominate background scattering. However, man-made structures are absent from most of the Earth's surface. Furthermore, existing methods identify PS pixels based on the similarity of their phase history to an assumed model for how deformation varies with time, whereas characterizing the temporal pattern of deformation is commonly one of the aims of any deformation study. We describe here a method for PS analysis, StaMPS, that uses spatial correlation of interferogram phase to find pixels with low-phase variance in all terrains, with or without buildings. Prior knowledge of temporal variations in the deformation rate is not required for their identification. We apply StaMPS to Volcán Alcedo, where conventional InSAR fails because of dense vegetation on the upper volcano flanks that causes most pixels to decorrelate with time. We detect two sources of deformation. The first we model as a contracting pipe-like body, which we interpret to be a crystallizing magma chamber. The second is downward and lateral motion on the inner slopes of the caldera, which we interpret as landsliding.Citation: Hooper, A., P. Segall, and H. Zebker (2007), Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcán Alcedo, Galápagos,

On 31 August a new eruption began from the same fissure and is still ongoing at the time of writing. After 4 September the movement associated with the dyke was minor, suggesting an approximate equilibrium between inflow of magma into the dyke and magma flowing out of it feeding the eruption. Minor eruptions may have occurred under Vatnajškull; shallow ice depressions marked by circular crevasses (ice cauldrons) were discovered in the period 27/08-07/09, indicating leakage of magma or magmatic heat to the glacier causing basal melting ( Fig. 1 and 2b). On 5 September, aircraft radar profiling showed that the ice surface in the centre of the B ‡r!arbunga caldera had subsided 16 m relative to the surroundings, resulting in a 0.32±0.08 km 3 subsidence bowl ( can be compared to a 1 day interferogram over the ice surface spanning 27 -28 August (Fig. 1), that has maximum line-of-sight (LOS) increase of 57 cm, indicating 55-70 cm of subsidence, during 24 hours. From 24 August to 6 September 16 M≥5 earthquakes occurred on the caldera boundary.Over 22000 earthquakes were automatically detected 16/08-06/09 2014, 5000 of which have been manually checked. Four thousand of these have been relatively relocated, defining the dyke segments. Ground deformation in areas outside the Vatnajškull ice cap, and on nunataks within the ice cap, is well mapped by a combination of InSAR, continuously recording GPS sites, and campaign GPS measurements. The GPS observations and analysis give the temporal evolution of the three-dimensional displacements used in the modelling (Fig. 1). Interferometric analysis of synthetic aperture radar images from the COSMO-SkyMed, RADARSAT-2 and TerraSAR-X satellites was used to form 11 interferograms showing LOS change spanning different time intervals (Supplementary Fig. 2). The analysis of seismic and geodetic data is described in Methods.Initial modelling of the dyke, with no a priori constraints on position, strike or dip, show the deformation data require the dyke to be approximately vertical and line up with the seismicity (Extended Data item 4). We therefore fixed the dip to be vertical and the lateral position of the dyke to coincide with the earthquake locations.We modelled the dyke as a series of rectangular patches and estimated the opening and slip on each patch ( Fig. 3a; see Supplementary Figures 3-4 for slip and standard deviations of opening). We used a Markov-chain Monte Carlo approach to estimate 7 the multivariate probability distribution for all model parameters (Methods) on each day 16/08-06/09 2014 (Fig. 2d). The results suggest that most of the magma injected into the dyke is shallower than the seismicity, which mostly spans the depth range from 5 to 8 km below sea level (see Fig. 2c and Methods). While magma may extend to depths greater than 9 km near the centre of the ice cap, towards the edge of the ice cap where constraints from InSAR and GPS are much better, significant opening is all shallower than 5 km (Fig. 3a). The total volume intruded into the dyke by 28 August was 0.48-0...