KEVIN REATH: 70% of the population died because they were unprepared for the eruption. If we had the instrumentation and the information that we have now at that volcano, they could have had some kind of forecast that an eruption would have occurred and evacuated the town. And all those people could've been saved. So essentially 20,000 lives could have been saved with these data.
This paper focused on three different data types-- thermal, degassing data, and deformation data, which is produced when the magma reservoir, before eruption it will expand sometimes. When that expansion happens it can get expressed on the surface. And we can see that with an instrument called InSAR.
One thing that I think this paper is going to be important for in the remote sensing community is that these three data types have never really been clearly intercompared. In the past, you might focus on maybe a year before one eruption or maybe two different eruptions. But we don't commonly see 17 years of time series data. The pre-eruptive period and the background period are very important because if you just had that one point of data, you don't necessarily know whether you're in the background or the pre-eruptive. And if you are in the pre-eruptive, that will give you time to prepare for a potential eruption that may happen in the future.
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Kevin Reath, a Cornell University postdoctorate associate and USGS Powell Center Fellow, studied 17 years of satellite data on volcanic activity in Latin America to propose a way to predict deadly eruptions before they occur.