How can citizen-scientists help with the prediction of future earthquakes?
Answers
Explanation:
We collectively have trouble understanding why disaster science, especially predictive science, is so far behind the tech curve, given its outsized importance to our lives. Part of the reason is that disaster science is incredibly complex! Whether we’re trying to harness atmospheric physics to understand the inner workings of a hurricane, or trying to understand the sociological complexities of keeping people safe in crises, there’s just no easy way to “predict” disasters.
But what about that old saying, “It takes a village to raise a child”? It occurred to me, as early as the 2004 Boxing Day Tsunami (also known as the Indian Ocean Tsunami), that a village could share the load of figuring this mess out instead of wholly relying on scientists and experts, especially in regions where scientists and experts might seldom be found. After all, when it comes to disasters, we’re definitely all in this together, like it or not.
Fifteen years later, along with co-authors Jonathan Sury, Mike James, Tamsin Mather and David Pyle, I’m proud to announce the publication of my first paper presenting evidence of what I’ve suspected all along: the “village” can indeed help predict disasters.
To find this out, we blended a few research methods in computer science, geography, and geohazards, and applied them to a hypothetical disaster situation to see if citizen scientists or the general public could help collect valuable terrain data, and whether that data would be any good for the purposes of disaster prediction.
Terrain models (3D digital representations of the Earth’s surface) are important for predicting potential disaster scenarios. Without terrain models, we can’t know where it might flood, how severe a landslide might be, or how quickly an avalanche can move.
The historic issue has been that terrain models are costly to make. Data for even a small study area can cost thousands, or likely tens of thousands, of dollars. Sometimes you can get terrain data for free, but often the tradeoff is that it’s lower quality and usually it’s not precise enough for predicting a disaster scenario. The commonly used free datasets derived from satellite missions would need to be 3 to 9 times more precise to give a good prediction for many disasters, such as landslides, avalanches, most volcanic phenomena, and flash floods. Some kinds of floods over large, flat areas can still be predicted reasonably well from lower resolution datasets, and little of the discussion here applies to disasters that happen below the Earth’s surface, such as earthquakes, or in its atmosphere, such as hurricanes. That said, it does apply to hazards that are related to and caused by earthquakes (landslides, rockfalls, etc.) or hurricanes (floods). The important distinction is to recognize where the hazard occurs: if it occurs at terrain level, then our article is relevant.