Quantifying Urban Activities Using Nodal Seismometers in a Heterogeneous Urban Space

Area of Science:

• Geophysics
• Urban Seismology
• Data Science

Background:

• Earth's surface exhibits vibrations from natural and anthropogenic sources.
• Anthropogenic vibrations are dominant in high-frequency seismic noise, showing temporal and spatial variability.
• Urban ambient seismic fields offer potential for monitoring human activities.

Purpose of the Study:

• To extract specific urban activities from ambient seismic noise using advanced signal processing.
• To analyze the high-resolution information within seismic data for urban activity monitoring.
• To investigate urban heterogeneity and societal response to disturbances like the COVID-19 pandemic.

Main Methods:

• Utilized advanced signal processing techniques on high-frequency ambient seismic noise.
• Extracted occurrence data for motor vehicle counts and runner activities.
• Compared seismic energy across frequency bands with extracted activity intensity within a 1km radius.

Main Results:

• Demonstrated the extraction of specific urban activities from seismic noise.
• Highlighted high-resolution spatial and temporal information present in seismic data.
• Observed intense heterogeneity in urban space and differential societal responses during the COVID-19 pandemic.

Conclusions:

• Ambient seismic fields provide a rich, anonymized data source for understanding urban dynamics.
• Advanced seismic analysis enables unprecedented spatial and temporal resolution for monitoring.
• Findings support the use of seismic data for dynamic urban management and policy-making.