Crowdsourcing and big data analytics aid search for Flight 370

DigitalGlobe, a commercial vendor of space imagery and geospatial content, based in Longmont, Colorado, US, maintains an image library containing 4.5 billion square kilometers of global imagery. Urgent calls from customers often initiate the search for a particular item: Within 90 minutes, DigitalGlobe can process geospatial big data and identify shapes like aircraft to aid rescuers during natural disasters and events.

The company operates a crowdsourcing website – called Tomnod – which they’ve activated in previous humanitarian efforts including Super Typhoon Haiyan. Tomnod mapped storm damage to buildings and roads throughout the Philippines, and provided important information to first responders, humanitarian groups, and governments.

With so much digital global coverage, it made sense to use the Tomnod platform to enable volunteers to help in the search for missing Malaysia Airlines Flight 370. DigitalGlobe is gathering as much human-created data as possible through crowdsourcing, running the collected data through big data filters and cluster analysis, and having experts determine if a certain spot requires investigation.

Malaysia Airlines Flight 370 disappeared during an 8 March flight from Kuala Lampur, Malaysia, to Beijing China. As of 15 March, the free-to-use Tomnod site indicated that 421,338 photos – each showing an area about 300 to 600 meters wide of the Indian Ocean – have been produced and entered into the analytics engine. To see current results or contribute to the search, visit tomnod.org.

- Amber Harmon