Earth Imaging Journal: Remote Sensing, Satellite Images, Satellite Imagery
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Crowdsourcing_Genghis

During the Genghis Khan crowdsourcing project, tags are color coded with roads (red) and rivers (blue) as well as ancient (yellow), modern (gray) and other (green) structures. Also shown is an example of peer feedback after a participant completes an annotation task.

Researchers at the University of California San Diego used satellite imagery for a crowdsourcing exercise to find Genghis Khan’s tomb. The project attracted more than 10,000 online volunteers for a combined total of 30,000 hours (3.4 years) spent analyzing the imagery, which was provided by the DigitalGlobe Foundation. The volunteers scanned imagery covering 6,000 square kilometers and generated 2.3 million feature characterizations.

The mechanisms and methodology are outlined in a new research paper, “Crowdsourcing the Unknown: The Satellite Search for Genghis Khan,” in the open access journal PLOS One. Crowdsourcing has proven effective for this type of exercise, particularly when fueled by a “charasmatic challenge,” such as finding Genghis Khan’s tomb. Also mentioned is DigitalGlobe’s survey for the missing Malaysia Airlines Flight MH370. More than 8 million participants surveyed over 1 million square kilometers looking for the missing aircraft.

Read the full paper for details on the system, methods and results.

 

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