Discussant: Zirou Zhou, Graduate Student, Department of Statistics, Iowa State University

Title: Preseason Crop Type Prediction Using Crop Sequence Boundaries

Abstract: This paper discusses the use of machine learning algorithms to predict crop types before the season begins, which has numerous applications in agriculture. The file includes information on the study area and crop types, the metrics used for evaluating model performance, experiments comparing the new field polygon-based approach with selected existing methods from the literature, and the benefits and limitations of field-level pre-season modeling. And we may expand this topic with NRI annual renew program, especially in using gradient boosting to predict the pre-season data.