Satellite AI models to improve global monitoring of drought, fire, and agriculture
Thematic Area: Environment
Faculty Advisor: Philip Dennsion, School of Environment, Society and Sustainability
Sierra Cutler will build AI and machine-learning models that preserve continuity between current and future satellite imagery of Earth’s surface and improve estimates of non-photosynthetic vegetation (NPV)—dead and dying plants, a key indicator of drought impacts, fire danger, farm practices, and more. She will use deep learning to map NPV from drone imagery. Then, she’ll use these maps to train a scalable model to estimate NPV in simulated imagery representing the higher-resolution satellite technology set to launch in 2031. The resulting open-source code and data will enable improved global monitoring of drought, fire, and agriculture.
Cutler began working toward her Ph.D. at the University of Utah last year, after she earned her master’s in geography from the U. She holds a bachelor’s in the same field from Brigham Young University.
