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Data from 3/11 could save lives if used effectively

by Philip Brasor

As the second anniversary of the Great East Japan Earthquake approached, the media again rallied to pay tribute to the tragedy’s victims, whether dead or alive. Many of the latter are still in limbo, unsure of their future since the events of that day wiped out much of their past. The tone of the coverage is bitter rather than hopeful, a function of the media’s mission to confront authority with its failures but also a manifestation of its natural predilection for melodrama. Amidst all this finger-pointing and hand-wringing, is it possible to learn anything useful?

Some information technology firms, media organizations and manufacturers combined resources last September for a project called Shinsai Big Data. Shinsai means “earthquake disaster,” and the “big data” is the information that was tracked on that fateful day from mobile phones, car navigation systems and social media. The volume was massive, and making sense of all the darting vectors and spinning integers is a daunting task, but experts in various information and infrastructure disciplines has been sifting through it all, not only to understand what happened on the ground that day but also what sort of measures can be implemented to prevent the same scale of suffering when it happens again. And it will happen again.

On March 3, NHK, which is involved in the project, aired a special that attempted to explain its findings so far. The conclusions are mostly speculative, since they are inferred from mathematical formulations. The “most shocking” implication of the car-navigation and mobile-phone data, according to one expert who has been collating them for months, is that many people who died in the tsunami at first moved away from the shoreline, just as they were supposed to do after the quake struck, but subsequently returned. He came to this conclusion by counting how many mobile-phone signals were present at 2:46 pm, when the quake occurred, in those areas that were later inundated, and then how many were present at different points of time when the giant waves arrived on land, depending on the location. Between 2:46 and a little after 3 pm, the number of signals decreased but thereafter started to go up, suggesting two scenarios: people moving away from the shoreline, and then others — or maybe the same people — moving back, presumably to help friends and family escape.

The car navigation data backs up the theory that individuals tried to save loved ones before the tsunami arrived. Secondary vectors described “V-movements” indicating vehicles that entered the disaster zones and picked up someone or something before changing direction. At the time of the quake there were an estimated 21,000 people in sections of Natori, Miyagi Prefecture, that would later be flooded by the tsunami, and data shows that there were about 21,500 people in those same sectors when the tsunami actually hit. Moreover, 2,500 people left the area but didn’t return, while 4,000 people from outside the area moved into it. Experts interviewed by NHK were disturbed by these findings, since they suggest many residents “didn’t follow evacuation protocols.” More than 1,000 people were killed by tsunami in Natori. The same pattern of movement applied to 24 other cities and towns.

No one in the documentary mentioned that the technology allowing experts to track the movements of victims may have had a bearing on their demise. The fact that these people owned automobiles spurred them to enter the danger zones, thinking that they could help others more effectively and quickly, but actually it sealed their doom. Data indicates that cars stopped moving just before the tsunami hit. The streets and bridges in these areas are narrow, and the greater congestion caused by the response to the quake led to gridlock. Many people who died in the affected areas were in their cars, likely waiting in traffic jams when the sea rushed in.

Other data indicate that some people traveled short distances within the disaster areas and stopped, meaning they did what they were supposed to do — move to the nearest evacuation points. But these points were originally designated without taking into consideration tsunami of this magnitude. Had these people moved to even higher ground — and they had enough time to do so — they would have survived.

Social media also provided valuable information both during the disaster and afterwards. The most famous related story is of the woman stranded with a group of disabled students in a building designated for evacuation who couldn’t get through to rescue services via normal channels and so sent an email to her son in London. He then tweeted his mother’s situation to followers in Japan, who retweeted the message until it reached officials in Tokyo, who then sent help. Apparently, there were numerous stories like this of trapped residents who used social networks to alert rescue workers, and one has to wonder about those who didn’t have access to such networks. When the Self-Defense Forces were combing the stricken areas for survivors, their searches were random and it’s assumed some people died while waiting for help.

The challenge for disaster management organizations will be administering this information when the next disaster strikes; that is, if they have access to it. There were 180 million tweets in Japan on 3/11. How should the authorities sort through such a mass of information? What sort of privacy considerations do they need to follow with regard to cellphone and GPS readings? Should it be made available to conventional media? Or are TV and radio less useful than they are thought to be? One of the more chilling findings of the Big Data project is that in the aftermath of the nuclear-plant accident some people actually moved toward areas of heavier fallout in response to mainstream media reports, which, due to their organizational size, are less nimble and flexible than targeted social media. Knowing what to pay attention to could save a lot of lives.

  • Rockne O’Bannon

    The author presents one instance of how data might be used, but there are so many other examples. There must be hundreds.

    Looking at electrical grid data, which areas came back up fastest and why are questions that can be answered easily.

    Warning systems can be enhanced by Twitter and other message systems if the traffic is monitored in real time for key words.

    The speed with which networks were used when they DID come up might show where emergency demand is highest. In future scenarios, given limited aid resources, it might be useful to know where that aid can best be used.

    Particularly with transport networks, it seems likely that trucking firms knew exactly where their shipments were when disaster struck. Having an automated system guiding those shipments to emergency centers instead of retail outlets would probably have prevented some waste of resources. Alternatively, rerouting shipments away from Tokyo, where people simply hoarded, to affected areas, where people truly needed help, would have been productive.

    Certainly the KINDS of information people need in a disaster could be inferred from key words used by searches made by people in affected areas.

    I was in the quake and subsequently affected area. We had very little information. Everyone else in the whole world did. It would have been nice if all those people had used every little bit of it to the greatest degree possible instead of focusing on Fukushima hysteria. Japan did very well. Japan can do better.

    The final paragraph of the article underscores that problem, doesn’t it? If people had paid more attention to government information, as we did, instead of mainstream media reports driven by uninformed hysteria, they would have been safer, by and large. Much, I would say almost all, of the mainstream media and relief organizations regarded the quake as a business opportunity and acted accordingly. Twitter, Google, etc. most certainly did not.