The purpose of this research is to develop and demonstrate the process of using sUAS-based remote sensing tools to detect and treat Elaeagnus umbellata on reclaimed mine lands. This project is based on similar principles used in precision agriculture, by implementing machine learning we will be able to identify and map Elaeagnus umbellata invasions; as well as employ the use of an UAS system configured for herbicide applications. The use of machine learning, specifically convolutional neural networks, are allowing researchers to handle problems that previously may have been too complex for traditional machine learning. Using a neural network, defining features and traits can be recognized through a computer program rather than known ecological or visual features. In this p