Researchers at the University of Florida — the flagship state university for the sinkhole capital of the nation — are developing artificial intelligence models to pinpoint early signs of sinkholes before they appear.
“I’m always looking for real-world problems,” said Minhee Kim, Ph.D., an assistant professor with the Department of Industrial and Systems Engineering, known as ISE. “We’re engineers, so we are always thinking, ‘What kind of new problem can we solve using data?’ And one of the more promising and relatively unexplored research areas is geomatics.”
Considered the bridge between earth science and engineering, geomatics refers to the application of geospatial technologies — satellite imagery, GPS and LiDAR (which measures distances to create 3D maps) — to collect and analyze geological data. But Kim and her team seek to expand those models to glean additional data to identify areas that are at risk of sinkholes.
The stakes are high.
Florida is prone to sinkholes because of the soluble bedrock — mostly limestone — under its surface. Rainwater dissolves it over time, creating underground cavities that, coupled with drought and other harsh conditions, cause the land to collapse.