Repeated periods of inflation‐deflation in the vicinity of Mt. Thorbjorn‐Svartsengi, SW‐Iceland, were detected in January–July, 2020. We used seismic ambient noise and interferometry to characterize temporal variations of seismic velocities (dv/v, %). This is the first time in Iceland that dv/v variations are monitored in near real‐time during volcanic unrest. The seismic station closest to the inflation source center (∼1 km) showed the largest velocity drop (∼ 1%). Different frequency range measurements, from 0.1 to 2 Hz, show dv/v variations, which we interpret in terms of varying depth sensitivity. The dv/v correlates with deformation measurements (GPS, InSAR), over the unrest period, indicating sensitivity to similar crustal processes. We interpret the velocity drop to be caused by crack opening triggered by intrusive magmatic activity. We conclude that single‐station cross‐component analyses provide the most robust solutions for early detection of magmatic activity.

A comprehensive catalog of historical earthquakes, with accurate epicenters and homogenized magnitudes is a crucial resource for seismic hazard mapping. Here we update and combine catalogs from several sources to compile a catalog of earthquakes in and near Iceland, in the years 1900–2019. In particular the epicenters are based on local information, whereas the magnitudes are based on teleseismic observations, primarily from international on-line catalogs. The most reliable epicenter information comes from the catalog of the Icelandic Meteorological Office, but this is complemented with information from several technical reports, scientific publications, newspaper articles, and modified by some expert judgement. The catalog contains 1272 $M_W \geq 4$ events and the estimated completeness magnitude is $M_W$ 5.5 in the first years, going down to $M_W$ 4.5 for recent years. The largest magnitude is $M_W$ 7.01. Such melting of local and teleseismic data has not been done before for Icelandic earthquakes, and the result is an earthquake map with no obviously mislocated events. The catalog also lists additional 5654 earthquakes on the Mid-Atlantic Ridge, north of 43\degree, with both epicenters and magnitudes determined teleseismically. When moment magnitudes are not available, proxy $M_W$ values are computed with $\chi^2$-regression, normally on $M_S$, but exceptionally on $m_b$. All the presented magnitudes have associated uncertainty estimates. The actual combined seismic moment released in the Icelandic earthquakes is found to be consistent with the moment estimated using a simple plate motion model. The catalog is named ICEL-NMAR and it is available online at http://dx.doi.org/10.17632/tg67sphksh.1.

Seismologists working with fiber-optic sensing, commonly referred to as Distributed Acoustic Sensing (DAS), have yet to find an established way of automatically detecting signals of interest within its recordings. We propose a new research perspective within the field by examining the output of a DAS array as an image and processing the image to find signals of interest. In this manuscript, we show an example of such a method, where we automatically detect seismic events of interest within two different DAS datasets, finding, respectively 99 % and 96 % of the local earthquakes previously identified within the data by manual analysis. The method is based on simple image processing and computer vision techniques, which clean the image, and, ideally, leave nothing but the signal of interest. These simple image processing steps yield promising results, indicating that computer vision and image processing might have an immediate impact in geophysical applications of fiber-optic sensing.