Crowdsourcing the Serengeti: How citizen scientists classified millions of photos from home

By Alexandra Swanson, University of Oxford | The Conversation

At this very moment in Serengeti National Park, Tanzania, more than 200 hidden cameras are snapping photos day and night, capturing the secret lives of the Serengeti’s most elusive animals. And, at this very moment, one of those cameras is probably getting chomped by a hyena. Such are the perils of being a camera trap in our Snapshot Serengeti survey.

The Serengeti is an incredibly diverse and dynamic ecosystem, famous for its high density of large carnivores and the annual migration of 1.6 million wildebeest and zebra.When we found ourselves with even more pictures than there are participants in that annual migration, we knew we had to figure out a way to classify and use all this information we were collecting. We turned to citizen scientists as a way to work through all these images and extract the valuable information they contain. Within three days of asking for the public’s help, we successfully processed an 18-month backlog of more than one million classifications.

With the help of about 30,000 volunteers who identified the images via the website Snapshot Serengeti, the first three years of data have been classified, catalogued and now published through Nature’s new journal, Scientific Data. This is the largest data set of its kind and would never have been possible without the help of the general public. A surfeit of snapshots.

As a graduate student in Ecology, Evolution, and Behavior at the University of Minnesota, I set 225 cameras to study how large carnivores shared the landscape with each other and their prey. Over the last five years, these remote, automatic cameras have captured more than two million images and more than 40 different animal species, providing an unprecedented look into the savanna wildlife ecology.Camera traps have revolutionized ecology and conservation research by providing a relatively low-cost method to monitor many different species across large areas. Triggered by a combination of heat and motion, when an animal walks by, these cameras snap a picture. Every photograph has a location, date, and time; by combining the information in these images, researchers can paint a picture of how many animals there are, where they are, and what they’re doing. With enough cameras and enough pictures, researchers can answer questions about how many different species interact to drive the incredibly complex dynamics of a natural ecosystem.

But “enough” data to answer complex ecological questions often means “too much” data for researchers to process. And, despite enormous recent advances in computer vision research, this type of complex pattern recognition remains something that the human brain is uniquely good at.Citizen scientists save the day

This is precisely the problem that I was facing: despite relentless vandalism by curious hyenas and elephants, the camera traps were capturing more pictures than I could possibly process alone, or even with a small army of undergraduate volunteers. So fellow ecologist Margaret Kosmala and I partnered with the world’s largest and most successful citizen science platform, The Zooniverse, to build Snapshot Serengeti.Like all Zooniverse projects, Snapshot Serengeti was designed to let anyone – not just experts – make valuable and reliable contributions. We asked users to identify and count the species that they saw in each photo. Volunteers could filter animals by body shape, color, pattern, even tail shape to narrow in on the best possible answer. On the discussion forums, they could talk with each other and with us about what they were seeing and why it mattered. This could all be done in their pajamas on the couch, since all they needed was an internet connection.