Data science competition for converting remote sensing to ecological data

Submissions are due by December 15, 2017 for the following Data Science Challenge

Scaling-up ecological patterns and processes is crucial to understanding the effects of environmental change on natural systems and human society. This Data Science Challenge pilot will include the use of NEON data in a challenge that multiple groups will attempt: to use the same remote sensing data from low flying airplanes to infer the location and type of trees in forests, and in turn, allow researchers to study forests in detail at much larger scales than is currently possible. This kind of collaborative data analysis challenge has proven highly effective in other fields for quickly improving methods for converting image data to useful information.

This challenge is sponsored by the National Institute of Standards Technology as part of it’s Data Science Evaluation series and is also partially supported by he Gordon and Betty Moore Foundation’s Data-Driven Discovery Initiative through grant GBMF4563.It uses data from the National Ecological Observatory Network in addition to data collected by the organizers. It is being organized by the Data Science Research lab, the Weecology lab, and Stephanie Bohlman’s lab all at the University of Florida.