Statistical Picking of Multivariate Waveforms.

In this paper, we propose a new approach based on the fitting of a generalized linear regression model in order to detect points of change in the variance of a multivariate-covariance Gaussian variable, where the variance function is piecewise constant. By applying this new approach to multivariate waveforms, our method provides simultaneous detection of change points in functional time series. The proposed approach can be used as a new picking algorithm in order to automatically identify the arrival times of P- and S-waves in different seismograms that are recording the same seismic event. A seismogram is a record of ground motion at a measuring station as a function of time, and it typically records motions along three orthogonal axes (X, Y, and Z), with the Z-axis being perpendicular to the Earth's surface and the X- and Y-axes being parallel to the surface and generally oriented in North-South and East-West directions, respectively. The proposed method was tested on a dataset of simulated waveforms in order to capture changes in the performance according to the waveform characteristics. In an application to real seismic data, our results demonstrated the ability of the multivariate algorithm to pick the arrival times in quite noisy waveforms coming from seismic events with low magnitudes.

Urban Seismic Network Based on MEMS Sensors: The Experience of the Seismic Observatory in Camerino (Marche, Italy).

Urban seismic networks are considered very useful tools for the management of seismic emergencies. In this work, a study of the first urban seismic network in central Italy is presented. The urban seismic network, built using MEMS sensors, was implemented in the urban district of Camerino, one of the cities in central Italy with the greatest seismic vulnerability. The technological choices adopted in developing this system as well as the implemented algorithms are shown in the context of their application to the first seismic event recorded by this innovative monitoring infrastructure. This monitoring network is innovative because it implements a distributed computing and statistical earthquake detection algorithm. As such, it is not based on the traces received by the stations from the central server; rather, each station carries out the necessary checks on the signal in real time, sending brief reports to the server in case of anomalies. This approach attempts to shorten the time between event detection and alert, effectively removing the dead times in the systems currently used in the Italian national network. The only limit for an instant alarm is the latency in the tcp/ip packages used to send the short reports to the server. The presented work shows the infrastructure created; however, there is not enough data to draw conclusions on this new early warning approach in the field, as it is currently in the data collection phase.

A Technological System for Post-Earthquake Damage Scenarios Based on the Monitoring by Means of an Urban Seismic Network.

A technological system capable of automatically producing damage scenarios at an urban scale, as soon as an earthquake occurs, can help the decision-makers in planning the first post-disaster response, i.e., to prioritize the field activities for checking damage, making a building safe, and supporting rescue and recovery. This system can be even more useful when it works on densely populated areas, as well as on historic urban centers. In the paper, we propose a processing chain on a GIS platform to generate post-earthquake damage scenarios, which are based: (1) on the near real-time processing of the ground motion, that is recorded in different sites by MEMS accelerometric sensor network in order to take into account the local effects, and (2) the current structural characteristics of the built heritage, that can be managed through an information system from the local public administration authority. In the framework of the EU-funded H2020-ARCH project, the components of the system have been developed for the historic area of Camerino (Italy). Currently, some experimental fragility curves in the scientific literature, which are based on the damage observations after Italian earthquakes, are implemented in the platform. These curves allow relating the acceleration peaks obtained by the recordings of the ground motion with the probability to reach a certain damage level, depending on the structural typology. An operational test of the system was performed with reference to an ML3.3 earthquake that occurred 13 km south of Camerino. Acceleration peaks between 1.3 and 4.5 cm/s2 were recorded by the network, and probabilities lower than 35% for negligible damage (and then about 10% for moderate damage) were calculated for the historical buildings given this low-energy earthquake.

A Lightweight Prototype of a Magnetometric System for Unmanned Aerial Vehicles.

Detection of the Earth's magnetic field anomalies is the basis of many types of studies in the field of earth sciences and archaeology. These surveys require different ways to carry out the measures but they have in common that they can be very tiring or expensive. There are now several lightweight commercially available magnetic sensors that allow light-UAVs to be equipped to perform airborne measurements for a wide range of scenarios. In this work, the realization and functioning of an airborne magnetometer prototype were presented and discussed. Tests and measures for the validation of the experimental setup for some applications were reported. The flight sessions, appropriately programmed for different types of measurements, made it possible to evaluate the performance of this detection methodology, highlighting the advantages and drawbacks or limitations and future developments. From the results obtained it was possible to verify that the measurement system is capable of carrying out local and potentially archaeological magnetometric measurements with the necessary precautions.

A Review of the Capacitive MEMS for Seismology.

MEMS (Micro Electro-Mechanical Systems) sensors enable a vast range of applications: among others, the use of MEMS accelerometers for seismology related applications has been emerging considerably in the last decade. In this paper, we provide a comprehensive review of the capacitive MEMS accelerometers: from the physical functioning principles, to the details of the technical precautions, and to the manufacturing procedures. We introduce the applications within seismology and earth sciences related disciplines, namely: earthquake observation and seismological studies, seismic surveying and imaging, structural health monitoring of buildings. Moreover, we describe how the use of the miniaturized technologies is revolutionizing these fields and we present some cutting edge applications that, in the very last years, are taking advantage from the use of MEMS sensors, such as rotational seismology and gravity measurements. In a ten-year outlook, the capability of MEMS sensors will certainly improve through the optimization of existing technologies, the development of new materials, and the implementation of innovative production processes. In particular, the next generation of MEMS seismometers could be capable of reaching a noise floor under the lower seismic noise (few tenths of ng/ Hz ) and expanding the bandwidth towards lower frequencies (∼0.01 Hz).

Multiple seasonality in soil radon time series.

The dynamics governing the movement of the radon are complex and dependent on many factors. In the present study, we characterise the nature of temporal variations of 2-hourly and daily radon measurements in several monitoring sites of the Italian Radon mOnitoring Network (IRON) in Italy. By means of continuous wavelet transformation, a spectral analysis in time-frequency domain is performed. The results reveal that there are sub-daily, daily and yearly persistent periodicities that are common for all the stations. We observe structural seasonal breaks, that occur at the same frequency but at distinct time. Variations in radon concentration and local temperature are studied in terms of frequency contents and synchronicity. When analysing several long time series together, it is evident that the phase difference at low frequency movements (365-day period) between the radon and local temperature time series is depending on the sites' location and therefore strongly controlled by local factors. This could at least partially explain the apparently contrasting results available in the literature obtained investigating smaller dataset about the relationships between temperature and radon variations. On the other hand, results show that all radon time series are characterised by marked cycles at 1 and 365-days and less evident cycles at 0.5-day and 180-days. They would be all ascribable to environmental-climatic factors: the short-period cycles to temperature and pressure variations, the long-period cycles also to seasonal rainfall variations.