New Strategy for Seismic Data

I’m a massive procrastinator and not a very quick thinker. There is something positive about all this. I’ve barely looked at code in the past few weeks, but have been thinking about it, and may well have saved some time. (I usually get there in the end…).

The neural net setup I had in mind was based on the assumption that I’d have my own, local, data sources (sensors). But hardware is still on hold until I find some funds. So I’ve been re-evaluating how best to use existing online data.

Now I am pleased with the idea of taking the VLF radio data as spectrograms and treating them (conceptually) as images, so I can exploit existing Deep Learning setups. If I’m not getting the seismic data as time series from a local sensor(s) but from INGV, I can use the same trick. They have a nice straightforward Web Service offering Open Data as QuakeML (XML) over HTTP from URL queries. They also render it like this:

seismo-map

So I’m thinking of taking the magnitude & depth data from the web service and placing it in a grid (say 256×256) derived from the geo coordinates. To handle the time aspect, for each cell in the grid I reckon picking the max magnitude event over each 6 (?) hour window. And then (conceptually) treating this as a pixel map. I need to read up a little more, but this looks again like something that might well yield to convnets, constructed very like the radio data input.

PS.

I made a little start on coding this up. First thing was to decide what area I wanted to monitor. Key considerations were: it must include here (self-preservation!); it must cover a fair distance around the VLF data monitoring station who’s data I’m going to use (Renato Romero’s, here); it should include the main seismically active regions likely to impact those two places.

You can get an idea of the active regions from the map above, here’s another one showing estimated risk:

hotspots

In one of the papers I’ve read that the radio precursors are only really significant for a 100km or so (to be confirmed), so I’ve chosen the area between the 4 outer markers here:

area

This corresponds to latitude 40N-47N, longitude 7E-15E.

The marker middle-left is the VLF station, the one in the middle is where I live.

It looked like the kind of thing where I could easily get my lats & longs mixed up so I coded up the little map using Google Maps, was very easy, source – rendered it on JSFiddle.

Next I need to get the code together to make the services requests, filter & aggregate the seismic event data is some convenient for ready for network training.

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Author: Danny Ayers

Web research and development, music geek, woodcarver. Originally from rural northern England, now based in rural northern Italy.

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