If there is one incident that has been consistently on the top deck of the 24x7 news flow for the last 12 days, it’s the one concerning Malaysian Airlines MH370, the aircraft that went missing on its way from Kuala Lumpur to Beijing with 239 passengers on board. This is because there is no evidence to conclusively prove any of the theories that have been floating around: From a suicide plan to a terror plot.
As of now, 26 countries are combing nearly 2.24 million nautical miles, from central Asia to the southern Indian Ocean. But this complicated search effort has a new arsenal in its kitty: An army of three million volunteers who are poring over high-resolution satellite imagery to detect the missing aircraft or any of its parts. Though this crowdsourcing has not yielded any result, the novel attempt will only boost the multi-national search operation.
Tomnod, which was once a research project of a US university and was later bought by a satellite imaging company, is spearheading the search. The format is simple: Once you log in to Tomnod and join the online search for the missing aircraft, you will see on your screen a small portion of the map, each tile is about the size of a city block. As a volunteer, you will have to look at the satellite image and tag anything that looks like wreckage, rafts, oil slicks, or other signs of the aircraft. If you do, then that particular satellite image will be sent to analysts who will then check the data and see if there is any trail that can be followed.
Tomnod already has 24,000 square-kilometres of hi-res imagery. On Tuesday, an Indian IT analyst said that he had seen a radar image of a plane flying very low above the Andaman Islands but nothing has come of it yet. Such crowdsourcing efforts are not new; it has been used earlier in disaster-hit locations, like in the Philippines after it was hit by the Super Typhoon Haiyan in November 2013.
While crowdsourcing cannot replace traditional search operations, it is a useful tool: Volunteers are eliminating areas that have no signs of debris, thereby helping to narrow down the search.