Happywhale enables wide area cooperation by integrating automation and crowd sourcing to deliver swift, laborsaving fluke ID recognition. Photo ID is a powerful tool, yet often produces large, backlogged data sets with high processing burdens. In response to these burdens, the web-based platform www.Happywhale.com develops and applies emerging options of automation, image recognition and crowd sourced human intelligence to image classification and management for increased accessibility, efficiency and consistency. The platform serves to gather, manage, and disseminate humpback whale photo-ID data where scientist and citizen scientist image contributors receive fast and accurate feedback and ongoing notifications of sightings. Citizen scientist engagement benefits the science by generating otherwise unavailable data while creating environmental education; collectively, as of March 2017, we have received submissions of 36,000 images from over 900 contributors, involving more than 9,500 encounters of over 4,500 identified individual humpbacks. The platform has been collecting worldwide data, with 87% of individually identified humpback whales coming from our focal region of the North Pacific. Happywhale aims to enable near-real-time catalog comparison and integration, together with new data generation to create an ocean-basin-wide ongoing linkage study building upon exiting datasets like the SPLASH study and the long-term study of humpback whales along the US West Coast. For the US West Coast this effort has been tightly integrated with ongoing scientific studies using photo-ID to better estimate humpback whale abundance, trends, movements, Distinct Population Segments, survivorship of entanglement/ship strikes and other human impacts. Happywhale has advanced humpback whale research and participation through crowd sourcing, automation, and swift individual ID image recognition with substantial labor savings, enabling efficient wide area collaboration.
Citation:
Cheeseman, Ted. J. Calambokidis, P. Clapham, F. Sharpe, T. Johnson, K. Flynn, K. Southerland, N. Muldavin. 2017. A new web-based platform for ongoing large-scale photo ID linkage study of North Pacific humpback whales. Abstract (Proceedings) 22nd Biennial on the Biology of Marine Mammals, Halifax, Nova Scotia, October 22-27, 2017.
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