IDTreeS Data Science Competition

Understanding and managing forests is crucial to understanding and potentially mitigating the effects of climate change, invasive species, and shifting land use on natural systems and human society. However, collecting data on individual trees in the field is expensive and time consuming, which limits the scales at which this crucial data is collected. Remotely sensed imagery from satellites, airplanes, and drones provide the potential to observe ecosystems at much larger scales than is possible using field data collection methods alone.

Because of this, Dr. Ethan White at the University of Florida is leading the second in a series of data science competitions aimed at identifying and classifying tree species from remote sensing images, and our lab is helping.

Read more about the competition and motivation behind it here