A recent CNN report announced thatNASA is asking for the help of citizens in viewing hundreds of thousands of images taken from space over the years, from the 1960s Mercury missions to the present images snapped from the International Space Station.
North Korea is barely lit when juxtaposed with neighboring South Korea and China.
Via The Gateway to Astronaut Photography of Earth, NASA is making these images available for citizens to examine.
NASA says the hope is that the images “could help save energy, contribute to better human health and safety and improve our understanding of atmospheric chemistry. But scientists need your help to make that happen.”
The catalog contains more than 1.8 million photos, about 1.3 million of them from the space station and roughly 30% of them taken at night.
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The CNN report said that before 2003, night images from the space station could be blurry, even with high-speed film and manual tracking, because the station moves at about 17,500 mph. In that same year, astronaut Don Pettit used a drill and assorted parts he found on the station to cobble together a “barn-door tracker,” a lower-tech predecessor to the European Space Agency’s NightPod, which was installed at the space station nine years later.
According to the report, NightPod’s motorized tripod compensates for the space station’s speed, providing what NASA scientist William Stefanov says are the highest-resolution night images from orbit. Satellites collect data more regularly, but the photos tend to be lower resolution. “Now the pictures are clear, but their location may not be, which limits their usefulness,” the NASA news release says.
Citizen science has a better handle on location than the night images from the space station and satellite imagery. The Complutense University of Madrid is spearheading efforts to get citizen input and organize the photos. They have broken down the the images into three components requiring different levels of participation:
1. Dark skies. This is the easiest project, as it requires no scientific expertise. “Anyone can help” by sorting the images into the categories: cities, stars or other objects, said Alejandro Sanchez, doctoral student at Complutense.
“Without the help of citizens, it is almost impossible to use these images scientifically. Algorithms cannot distinguish between stars, cities and other objects, such as the moon. Humans are much more efficient for complex image analysis,” he said.