Montserrat Mountain is located near Barcelona in Catalonia, in the northeast of Spain, and its massif is formed by conglomerate interleaved by siltstone/sandstone with steep slopes very prone to rockfalls. The increasing number of visitors in the monastery area, reaching 2.4 million per year, has highlighted the risk derived from rockfalls for this building area and also for the terrestrial accesses, both roads and the rack railway. A risk mitigation plan has been launched, and its first phase during 2014-2016 has been focused largely on testing several monitoring techniques for their later implementation. The results of the pilot tests, performed as a development from previous sparse experiences and data, are presented together with the first insights obtained. These tests combine four monitoring techniques under different conditions of continuity in space and time domains, which are: displacement monitoring with Ground-based Synthetic Aperture Radar and characterization at slope scale, with an extremely non-uniform atmospheric phase screen due to the stepped topography and atmosphere stratification; Terrestrial Laser Scanner surveys quantifying the frequency of small or even previously unnoticed rockfalls, and monitoring rock block centimetre scale displacements; the monitoring of rock joints implemented through a wireless sensor network with an ad hoc design of ZigBee loggers developed by ICGC; and, finally, monitoring singular rock needles with Total Station.Peer ReviewedPostprint (author's final draft
Abstract. During the COVID-19 pandemic
lockdown, the city of Barcelona was covered by a dense seismic network consisting of up to 19 seismic sensors.
This network has provided an excellent tool to investigate in detail the
background seismic-noise variations associated with the lockdown measures.
Permanent stations facilitate comparing the seismic noise recorded during
the lockdown quieting with long-term variations due to holiday periods. On
the other hand, the data acquired by the dense network show the differences
between sites located near industrial areas, transportation hubs or
residential areas. The results confirm that the quieting of human activity
during lockdown has resulted in a reduction in seismic vibrations in the
2–20 Hz band that is clearly higher than during holiday seasons. This effect is
observed throughout the city, but only those stations not affected by very
proximal sources of vibration (construction sites, industries) are clearly
correlated with the level of activity denoted by other indicators. Our
contribution demonstrates that seismic amplitude variations can be used as a
proxy for human activity in urban environments, providing details similar to
those offered by other mobility indicators.
Abstract. The city of Barcelona has been covered during the COVID-19 pandemic lockdown by a dense seismic network consisting of up to 19 seismic sensors. This network has provided an excellent tool to investigate in detail the background seismic noise variations associated to the lockdown measures. Permanent stations facilitate to compare the seismic noise recorded during the lockdown quieting with long-term variations due to holiday periods. On the other hand, the data acquired by the dense network show the differences between sites located near industrial areas, transportation hubs or residential areas. The results confirm that the quieting of human activity during lockdown has resulted in a reduction of seismic vibrations in the 2–20 Hz band clearly higher than during holiday seasons. This effect is observed throughout the city, but only those stations not affected by very proximal sources of vibration (construction sites, industries) are clearly correlated with the level of activity denoted by other indicators. Our contribution demonstrates that seismic amplitude variations can be used as a proxy for human activity in urban environments, providing details similar to those offered by other mobility indicators.
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