By looking at a city’s magnetic footprint, it’s possible to keep an eye on its health, including as a possible early warning system for pollution problems and a way to save the most energy.
Researchers from the United States and Germany provide a comparison investigation of urban magnetic fields between two U.S. cities: Berkeley, California, and the Brooklyn borough of New York City, in the Journal of Applied Physics from AIP Publishing. They look at what kinds of information can be derived from magnetic field sensor data in order to better understand how cities work and provide insights that could be used for preventative studies.
Cities are well-known for their tremendous noise levels, making them ideal environments for studying about urban science. Magnetic field activity from numerous sources throughout the city can reveal what is going on throughout the course of a 24-hour period.
“A city is viewed as a physical system akin to a distant astronomical object that can be studied using a variety of multispectral techniques,” Lawrence Berkeley National Laboratory’s Vincent Dumont explained. “In short, our project was inspired by our desire to apply what we learned practicing fundamental physics research to the study of cities.”
Researchers used synchronized measurements with a network of sensitive magnetometers to capture magnetic field data constantly during a four-week period. Modern data analysis techniques were used to process and analyze the data.
In their present research comparing two very different cities, Brooklyn and Berkeley, they discovered that Berkeley’s magnetic field activity drops to near zero during the night, whereas Brooklyn’s magnetic field activity remains constant throughout the day.
“Again, not too surprisingly, we discovered that ‘New York never sleeps,’ or more seriously, there are indeed a number of magnetic signatures specific to each city,” he explained.
The researchers hope that their combination of network magnetometry and smart data analysis can become a useful tool for urban science that draws on many different fields.
“This work builds on our earlier experiments conducted around the city of Berkeley, in the San Francisco Bay Area,” Dumont added. “We identified the dominant sources of magnetic signals – which, not too surprisingly, turned out to be the trains of the Bay Area Rapid Transit (BART) system, and learned to glean weaker signals from this dominant background.”
“We hope this line of research will be picked up and further developed both by the members of our team as well as others, hopefully within cities around the world,” he noted.
This strategy to studying cities through their noise using data from magnetic field sensors has evolved in recent years, and it has been pursued by the Center for Urban Science and Progress in New York.
The Laser Interferometer Gravitational Wave Observatory experiment, which looks for gravitational waves, and the Global Network of Optical Magnetometers for Exotic Physical Searches collaboration, which looks for dark matter, are two examples of techniques that use data from magnetic field sensors.
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