 This study compared two popular machine learning algorithms, support vector machines, SVM and random forests, RF, to identify tree species in two different forests. Both algorithms achieved high accuracy rates, with SVM performing slightly better than RF. Additionally, the study found that increasing the number of training samples improved the performance of both algorithms. This article was authored by Laurel Ballanti, Leonard Bleusius, Ellen Hines, and others.