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If it is true that the plane continued to fly for several hours after all contacts (including radar) were lost, presumably landing successfully in a secret location, here is how data science could help.
From the point where contact was lost, simulate all potential paths (limited by amount of gas available in the gas tank) that the plane could have followed to avoid radar detection. In short, create a map of "no radar signal" (similar to maps showing no cell phone reception), and focus on paths that end up on land (rather than on sea, though the pirates could also have landed on sea outside of any country, stealing all valuables from the plane, then sink the plane, and board a vessel or submarine to reach the land).
Vincent, a water landing is definitely not like the movies. Probability of a non-breakup or floater is negligible.
What we need is a repeat of Cmdr. Dr. Craven and the search for the USS Scorpion ( http://en.wikipedia.org/wiki/USS_Scorpion_(SSN-589) ). Crowd wisdom.
I didn't know about the Scorpion. I had read of a similar one where they used Bayesian approaches. Actually, I just came across something:
Fascinating stuff. So unfortunate, though.
Thomas - excellent book on it: "Blind Man's Bluff, by Sherry Sontag and Christopher Drew.
Comment from one of our members:
There's also the fact, I believe already raised in some discussions, that many of the passengers carried mobile phones (which are allegedly mysteriously ringing and connecting before being disconnected). Granted this may be a vagary of the telecoms system in the area, but with that many mobile phones there's another option for triangulation that may not have been immediately switched off. Surely among all those passengers there would've been at least one who didn't go to airplane mode or turn it off entirely. Some smartphone apps also regularly 'check in' and/or maintain contact with the cloud - considering the high profile nature of this, I'm wondering if Apple or Google android could tweak their systems to generate a list of what apps were on those phones for the LEO's involved, which would could be compared to find which had such apps, and source the last 'check in' time and location of them, making another potential data source to build the track.
Vincent, your proposal seems to be predicated on the assumption that all radar data is being shared 1) among governments, and perhaps 2) with the public. Perhaps some government has radar data which it is not sharing for whatever reason, to include such possibilities as collusion in the plot or embarrassment at the action or lack thereof which it took in response to such radar data. Additionally, not all governments wish to share the capabilities and limitations of their radars and other surveillance assets, nor the manner in which they are employed, their operational availability and readiness (whether good or bad).
Looking at real data from the past 100 years of aviation incidents is an eye-opening way to get a more rational perspective on this international tragedy. I created a dashboard with data from multiple data sources (ACI, Aviation Safety Network, and Openflights.org) using a business intelligence tool, so it’s easy to visualize and analyze the information of approximately 20,000 flight incidents in the past 100 years, from commercial to military and in airports all around the world, and gain incredible insights on a century of aviation: There have been around 100 missing flights around the world in the past century, most of which were small, private flights that are harder to track, with an average of 13 fatalities per flight. The total number of fatalities on missing passenger flights is roughly 1,324, and the highest single incident had 69 fatalities.
Possibly the most shocking news of all is that considering 13 is the average number of fatalities for missing flights, MH370 is statistically the most tragic missing flight incident with the highest fatality rate in a single incident that (may have) ever occurred. It is also important to note that missing flights is considerably rare, especially ones carrying more than about 50 passengers.
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You might want to check out this Wikipedia entry. Not the same data, but insightful.