It is estimated that in the two decades between 1993 and 2014, there were 1.35 million deaths attributed to natural disasters, which is roughly 68,000 lives lost per year. Natural disasters have also affected close to 218 million people around the globe in the 20-year period.
Of all the types of natural disasters, one proves more devastating than the others: earthquakes. “Earthquakes killed more people than all other types of disaster put together, claiming nearly 750,000 lives between 1994 and 2013,” reports the International Relief Web. Of those, the Tsunami category is the most deadly sub-type of earthquake, with an average of “79 deaths for every 1,000 people affected, compared to four deaths per 1,000 for ground movements.”
Scientists, researchers and disaster relief experts have long looked for ways to better forecast earthquakes before they hit in order to reduce the amount causalities. “Earthquake prediction relied almost entirely on monitoring the seismic frequency and using this to establish when earthquakes are most likely to happen – until now.” This as written by Nav Dhunay, innovative tech entrepreneur and founder of Ambyint, in a recent TechVibes write-up.
As Nav Dhunay points out in his TechVibes article, technological innovations are revolutionizing the way scientists are able to collect data. “Big Data analysis has begun to open up a plethora of opportunity for earthquake forecasters who are now able to statistically analyze satellite and atmospheric data to predict earthquakes accurately anywhere around the world,” writes Nav Dhunay, whose Ambyint proprietary technology utilizes Big Data analytics.
Big Data is already helping scientists increase their accuracy in predicting earthquakes and the duration of time they can give those who will be affected. “Companies such as Terra Seismic carry out real-time monitoring of satellite data and environmental factors which they say allow them to predict earthquakes anywhere in the world with 90% accuracy,” writes Forbes Magazine’s Bernard Marr.
These advances have also allowed scientists the ability to forecast earthquakes one to 30 days in advance, which in turn significantly reduces casualty levels. Researchers are hoping to increase this window of time so all those in the predicted zone may be evacuated efficiently.
Another innovative program that is being implemented is Smart Oceans BC, a Canadian program that aims to utilize Big Data analytics to monitor the seafloor for seismic activity, as well as a variety of other quantitative data. “The four key elements of disaster management are prevention, preparation, response and recovery. Big Data has potential to help with all of them,” states Marr.
Response is another area of disaster management that is being impacted by the capabilities of Big Data. The technology was invented after the earthquake that devastated Japan 2011, when a university student realized public data paired with Big Data can be used to monitor where those fleeing devastated areas flee to in order to provide aid and assistance. “Using GPS data from 1.6 million mobile phones, Song and his colleagues at the University of Tokyo built a model that can now predict where individuals in cities all over Japan will go when the next earthquake strikes,” writes Sydney Brownstone for Coexist.
In addition to the thousands of lives that are lost every year from earthquakes, $12 billion dollars in economic activity is also lost. Big Data will not only save lives, it will help mitigate financial losses in areas that have been affected by natural disasters.
