Discovery Summit China
12 April 2018
Projections and Encapsulations
John Sall, Co-Founder and Executive Vice President, SAS
As our tables get more numerous, our data gets bigger and our models have more features to encapsulate, we are looking for improvements to organize, contain and model. With the release of JMP 14, there are new ways to do all this.
FIT in JMP: Monitoring giant panda populations
Sky Alibhai, Director and Co-Founder, WildTrack
Zoe Jewell, President and Co-Founder, WildTrack
Binbin Li, Assistant Professor of Environmental Sciences of the Environmental Research Center, Duke Kunshan University
Arguably the world’s most iconic species, the giant panda needs help. And to help this endangered species, conservationists need reliable data on numbers and distribution. That's where WildTrack and Duke Kunshan University scientists come into play. Together with researchers from the Chinese government, these scientists employ a cost-effective, non-invasive and community-friendly footprint identification technique to collect footprint data from giant pandas. Then WildTrack builds highly accurate algorithms to classify individuals and determine their sex, which is the most successful giant panda data collection and analysis method to date. Yet the conservation methods continue to evolve, deploying high-resolution drones to capture footprints in previously inaccessible areas, and exploring the application of deep learning to help filter increasing volumes of data as they come in. This work helps provide a promising future for wild panda populations and the protection of the other species that share this habitat that hosts some of the richest biodiversity on earth.