On the crowdsourcing of macroseismic data to characterize geological settings

Abstract

Macroseismic data are obtained from observing the effects of an earthquake on people, buildings, and the natural environment. The crowdsourced macroseismic data are collected from a large number of people, often through online platforms or mobile applications. These data can be useful for characterizing geological features, depending on several factors, such as the quality of the data, the representativeness of the sample, and the methods used for data collection and analysis. As a case study, we consider the macroseismic data collected in Trieste (NE Italy) through online questionnaires completed by citizens after the 2020 Mw 6.4 earthquake in Petrinja (Croatia). The campaign was promoted through social media and in a short period of time more than 6000 questionnaires were completed by the citizens of Trieste. The analyzed macroseismic data show good agreement with the expected seismic response of the main soil types of the city. A comparison with a similar project we conducted in Trieste in 2012, following the 2012 Emilia May 20 and 29 earthquakes, shows that also in that case, although a much smaller number of questionnaires was collected, the main characteristics identified correspond well with the soil types of Trieste. Thus, our study proves the importance of collecting macroseismic data even in areas of low damage. Moreover, it shows how people's early engagement, computer skills, social networks, and smartphone popularity can influence the results of such data collection and opens new scenarios for a better understanding of earthquake risks and improved awareness and preparedness through citizen participation.