Path and site effects deduced from merged transfrontier internet macroseismic data of two recent <i>M</i>4 earthquakes in northwest Europe using a grid cell approach

Abstract

Abstract. The online collection of earthquake reports in Europe is strongly fragmented across numerous seismological agencies. This paper demonstrates how collecting and merging online institutional macroseismic data strongly improves the density of observations and the quality of intensity shaking maps. Instead of using ZIP code Community Internet Intensity Maps, we geocode individual response addresses for location improvement, assign intensities to grouped answers within 100 km2 grid cells, and generate intensity attenuation relations from the grid cell intensities. Grid cell intensity maps are less subjective and illustrate a more homogeneous intensity distribution than communal ZIP code intensity maps. Using grid cells for ground motion analysis offers an advanced method for exchanging transfrontier equal-area intensity data without sharing any personal information. The applicability of the method is demonstrated on the felt responses of two clearly felt earthquakes: the 8 September 2011 ML 4.3 (Mw 3.7) Goch (Germany) and the 22 May 2015 ML 4.2 (Mw 3.7) Ramsgate (UK) earthquakes. Both events resulted in a non-circular distribution of intensities which is not explained by geometrical amplitude attenuation alone but illustrates an important low-pass filtering due to the sedimentary cover above the Anglo-Brabant Massif and in the Lower Rhine Graben. Our study illustrates the effect of increasing bedrock depth on intensity attenuation and the importance of the WNW–ESE Caledonian structural axis of the Anglo-Brabant Massif for seismic wave propagation. Seismic waves are less attenuated – high Q – along the strike of a tectonic structure but are more strongly attenuated – low Q – perpendicular to this structure, particularly when they cross rheologically different seismotectonic units separated by crustal-rooted faults.

Evaluation of macroseismic intensity, strong ground motion pattern and fault model of the 19 July 2019 Mw5.1 earthquake west of Athens

“…Due to irregular geographic pattern of the assigned intensities in the entire prefecture of Attica and the damaged buildings distribution to the east, south and southeast of the epicentre, identification of any spatial clustering was considered necessary. Geographical coordinates of intensity sites and geocoded addresses of damaged buildings allowed for their grouping within grid cells, following the approach proposed by Wald et al (1999aWald et al ( , 2011, who subdivided uneven ZIP code areas into regularly sized grids of a few kilometres and Van Noten et al (2017), who assessed intensity at 100 km 2 grid cells. For the studied earthquake, the dense population distribution of Athens metropolitan allowed the selection of grid cells size at 4.957 km 2 , each containing more than 3 intensity values and/or at least 3 damaged buildings.…”

“…Given that individual intensity values include a certain degree of inherent uncertainty, EMSC and NKUA intensities were averaged per cell, according to the EMS98 practice (Grünthal 1998;Van Noten et al 2017), but only for those cells that contain IDPs and had no damaged buildings. No significant effects are expected due to such averaging, as IDPs values do not exceed one EMS98 degree of difference in each cell.…”

The damaging character of shallow 20th century earthquakes in the Hainaut coal area (Belgium)

“…Fortunately, the availability of the ROB online Did You Feel It? inquiry since 2002 (Camelbeeck et al, 2003;Lecocq et al, 2009) can resolve this granularity as street addresses of testimonies can be geocoded and intensity data can be aggregated in size-adaptable grid cells (Van Noten et al, 2017). For potential future events, this strategy might allow oversampling the macroseismic field and modelling the intensity variability in each commune, except in localities with extensive damage (cf.…”

Analysis of Online News Coverage on Earthquakes Through Text Mining

“…Enhanced applications of tools such as this can have alternative uses of far more important implications than just statistical analysis aimed at finding which earthquake is being reported. For example, it can be used to automatically map the felt intensity of an earthquake-struck region based on the macroseismic scale, traditionally limited to people filling in local felt report forms (e.g., Wald et al, 2012;Bossu et al, 2016;Van Noten et al, 2017). Another use could be to detect mistaken news reports about wrongly reported seismic activity such as the case with Kenya's "crack" in 2018 2,3,4 , whereby the reports can be validated automatically with earthquake bulletins.…”