I run two online citizen science projects: Snapshot Serengeti (ongoing since December 2012) and Season Spotter (ongoing since July 2015). I am also an advisor to Jungle Rhythms (ongoing since November 2015).

Snapshot Serengeti

Hundreds of camera traps in Serengeti National Park, Tanzania, are providing a powerful new window into the dynamics of Africa’s most elusive wildlife species. We need your help to classify all the different animals caught in millions of camera trap images.

Ali Swanson and I started planning what would become Snapshot Serengeti late in 2011 and we built the site in partnership with the Zooniverse the next  year. Since its launch in December 2012, this citizen science project has proven enormously successful. More than 5 million images have been processed by 30,000+ volunteers. These images are from a grid of 225 camera traps across an 1,125 sq-km region of central Serengeti National Park in Tanzania taken over 4 years. Almost 50 species and species groups  are represented in the citizen science data, including all large and medium sized mammals. We’re very excited about the potential of the resulting datasets in informing community ecology research, conservation, citizen science data processing, and computer vision research. Our initial launch and the publication of our first dataset garnered attention from BBC News, Washington Post, New York Times, Newsweek, LA Times, the Daily Mail, the New Yorker, International Business Times, PBS Newshour, Public Radio International, CBS News, Discovery News, WIRED, Discover Magazine, Science Daily, Scientific American, National Geographic, Smithsonian News, Huffington Post, USA Today, the Wildlife Society, Boing Boing, SlashGear, and many others, including in multiple languages and in overseas media outlets in Europe, Asia, and South America.

Season Spotter

By identifying images with changing leaves, blooming flowers, and other easy-to-recognize features, you will contribute to a better understanding of how plants are responding to climate change.

I built Season Spotter while a postdoc in Andrew Richardson’s lab, funded by an NSF Macrosystems grant to Andrew, Sandra Henderson, and Robert Pless to specifically do citizen science using the PhenoCam network. This network comprises more than 200 elevated automatic cameras deployed throughout North America (and increasingly beyond) to record foliage from all different ecosystems hourly throughout the years. Season Spotter was created as a way to augment automated processing of PhenoCam images to uncover new information in them, as well as to ground-truth automated techniques and explore new frontiers in automated phenology data collection and processing. I built it in partnership with the Zooniverse, using its novel citizen science project builder.