On the Effectiveness of Crowd Sourcing Avian Nesting Video Analysis at Wildlife@Home

Abstract

Abstract Wildlife@Home is citizen science project developed to provide wildlife biologists a way to swiftly analyze the massive quantities of data that they can amass during video surveillance studies. The project has been active for two years, with over 200 volunteers who have participated in providing observations through a web interface where they can stream video and report the occurrences of various events within that video. Wildlife@Home is currently analyzing avian nesting video from three species: Sharptailed-Grouse (Tympanuchus phasianellus) an indicator species which plays a role in determining the effect of North Dakota's oil development on the local wildlife, Interior Least Tern (Sternula antillarum) a federally listed endangered species, and Piping Plover (Charadrius Melodus) a federally listed threatened species. Video comes from 105 grouse, 61 plover and 37 tern nests from multiple nesting seasons, and consists of over 85,000 hours (13 terabytes) of 24/7 uncontrolled outdoor surveillance video. This work describes the infrastructure supporting this citizen science project, and examines the effectiveness of two different interfaces for crowd sourcing: a simpler interface where users watch short clips of video and report if an event occurred within that video, and a more involved interface where volunteers can watch entire videos and provide detailed event information including beginning and ending times for events. User observations are compared against expert observations made by wildlife biology research assistants, and are shown to be quite effective given strategies used in the project to promote accuracy and correctness.