NASA space data can reduce disaster response time

Emergency responders could cut costs and save time by using near-real-time satellite data along with other decision-making tools after a flooding disaster, says a new study.

Using the 2011 Southeast Asian floods as a case study, the researchers calculated the time that could have been saved if ambulance drivers and other emergency responders had near-real-time information about flooded roads.

Ready access to this information could have saved an average of nine minutes per emergency response and potential millions of dollars, said the study published in the journal Frontiers in Environmental Science.

The study is a first step in developing a model to deploy in future disasters, according to the researchers.

"We chose data that represented what we would know within a couple hours of the event," said the study's lead author Perry Oddo, an associate scientist at NASA's Goddard Space Flight Center in Greenbelt, Maryland.

"We took estimates of flood depth and damage and asked how we could apply that to route emergency response and supplies. And ultimately, we asked, what is the value of having that information?"

In 2011, heavy monsoon rains and La Nina conditions across Southeast Asia's Mekong River basin inundated and destroyed millions of acres of crops, displacing millions of people and killing hundreds.

The researchers investigated how access to near-real-time satellite data could have helped in the aftermath of the floods, focusing on the area surrounding Bangkok, Thailand.

"The response time for emergency responders is heavily dependent on the availability and fidelity of the mapped regions," said John Bolten, associate program manager of the NASA Earth Science Water Resources Program, and the study's second author.

"Here we demonstrate the value of this map, especially for emergency responders, and assign a numeric value to it. It has a lot of value for planning future response scenarios, allowing us to move from data to decision-making," Bolten said.IANS