DSFAS: A GLOBALLY AVAILABLE, LOCALLY TAILORED CROP EVAPOTRANSPIRATION FORECAST TOOL

The overall goalof this project is todevelopanddelivera proof-of-concept model for globally available crop ET forecasts based on smartphone images and tailored to local soil moisture conditions using deep learning (DL).To accomplish our overall goal, we will focus on three objectives:Extend existing methods to forecast site-specific crop ET for well-watered conditions anywhere globally. Develop a deep learning model to estimate crop water stress based on recent weather and images provided by the farmer.Deliver the proof-of-concept model and collect feedback.