How Big Data Speeds Disaster Response.
A hurricane slams a coastal city with wind, rain, and waves. People are trapped on rooftops or cut off from food and water. But roads are blocked. Cell phone calls can’t get through. Those responding to an emergency need to know where the worst damage is. This helps them quickly repair the services that keep people safe. Have three hospitals lost power, or only two? Is one of them completely destroyed? Are the fire stations operating? Which nursing home, or sewage treatment plant, is under water? And which roads and bridges are still open for delivering precious electric generators, water, and other supplies?
TIME AND PLACE
These questions are all related to geography: where things are on the Earth, what shape they’re in, and how to reach them. Maps usually help us with this, but they aren’t as straightforward as you’d think—especially after a tornado has scrambled a neighborhood or a flood has carried homes miles downstream. Now where is a building—or the person who lives there—and how do rescuers and officials find them?
The Federal Emergency Management Agency (FEMA) is in charge of directing recovery after national emergencies like the devastating 2017 hurricanes in Texas, Florida, and Puerto Rico. But FEMA also helps handle other kinds of natural disasters, like earthquakes, forest fires, and tornadoes.
When attempting to face the death and destruction these disasters cause, FEMA also has to face a data problem. Often the local people FEMA works with to make decisions are using different maps, kept in different forms. Each county tracks local properties in its own way.
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Bu hikaye Muse Science Magazine for Kids dergisinin November/December 2018 sayısından alınmıştır.
Start your 7-day Magzter GOLD free trial to access thousands of curated premium stories, and 9,000+ magazines and newspapers.
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