What is VIEWS ?

1. Infrasound array monitoring

Infrasonic waves are generated by volcanic explosive activity due to the coupling between the magma and atmosphere. Unlike seismic waves, which are generated by both surface and internal volcanic processes, infrasound waves unmistakably reveal surface volcanic activity. Small-aperture infrasonic arrays, consisting of 3-4 infrasound sensors, are in turn capable of effectively measuring and localizing the explosive activity from remote positions (up to 10km from the crater), making it a powerful monitoring technique (Ripepe et al. 2007). Such array processing methodology, is in particular capable of monitoring explosive volcanic activity in real-time (nowcasting), and also provides the opportunity to anticipate potential risk scenarios (forecasting / early-warning).

The infrasonic parameter IP, which accounts for the rate, intensity, and location of the infrasounds detected by the array, was specifically developped to quantify volcanic explosive activity. In turn, an infrasonic Early Warning System was developped at Etna volcano (Ulivieri et al. 2013, Ripepe et al. 2018), where IP threshold values and early warning criteria have been developed and validated to anticipate potential ash injection scenarios into the airspace. Over the past ~15 years, the system has provided real-time automatic notifications of volcanic explosive activity to governmental agencies (Civil Protection) and juridictions in charge of the airspace (Catania airports).

Since 2026, the Early Warning system has been replicated at Popocatépetl volcano (Mexico) and integrated within the MOUNTS platform, thereby providing real-time quantification of the explosive activity. The automatic alert messaging system (Telegram) is restricted to interested users.

The implementation of the Infrasonic Early Warning Sytem within MOUNTS results from a collaboration between different entities:

• LGS: The Laboratory of Experimental Geophysics LGS (University of Firenze UNIFI, Italy), led by Prof. M. Ripepe, has been studying volcanic infrasounds for over 25 years. Throughout the years, it has acquired global recognition for its expertise in infrasounds, spanning practical (i.e., sensor development and field deployment) and theoretical (i.e., data processing, infrasound generation and propagation theory) aspects. It has made extensive use of infrasound for real-time monitoring of volcanic activity, including permanently operating arrays (Stromboli and Etna, mandated by the Italian Civil Protection), and temporary measurement campaigns in 15+ countries across the globe.
• GECO: The GECO company is specialized in the geophysical monitoring of natural hazards, through the development of hardware, software, and scientific consultancy. It is in particular responsible for the Infrasonic Early Warning System at Etna since 2020 (Etna App), through a collaboration with LGS.
• UNAM / MOUNTS: Throughout the PAPIIT project IA102221 ("Linking space and ground-based observations for better understanding and prediction of eruptive crises", UNAM-DGAPA), and more recently the SECTEI project ("Sistema de monitoreo de la actividad explosiva volcánica del Popocatépetl mediante infrasonidos", SECTEI), both led by Sébastien Valade (Instituto de Geofísica, UNAM), the infrasound monitoring system at Popocatépetl volcano was implemented and integrated within the MOUNTS ecosystem. The processing algorithm for the Infrasonic Early Warning system, mainly developed by G. Ulivieri (former LGS member, now GECO) and operating at Etna volcano since 2013, was shared with S. Valade, who implemented it in the MOUNTS ecosystem and adapted it for monitoring Popocatépetl.

2. Seismic monitoring

Seismic waves are generated by both subsurface dynamics associated with magma movement, and surface processes associated with volcanic activity. VIEWS integrates the calculation of seismic parameters such as the tremor (RMS amplitude between 1-10 Hz), which is commonly used to track the volcanic activity in open-systems (e.g. Valade et al. 2016). In addition, preliminary integration of deep-learning based classification of seismic activity is achieved through fine-tuning of the VOISS-NET model (Fee et al. 2025).

3. Webcam monitoring

Visual monitoring complements geophysical signals by detecting eruptive products, such as ash ash emissions, lava flows, etc. A deep-learning based segmentation model of webcam images was recently developed (Giffard-Roisin et al. 2026), and will soon be fine-tuned and integrated within the VIEWS framework.