The invasive reed Phragmites australis ssp. australis is forcing its way into many of North America’s wetlands, displacing native species and leading to extreme ecosystem regime shifts[1]. Phragmites is a typical example of an invasive plant disrupting native communities through competitive exclusion, niche displacement, etc. Rapid detection and management response is imperative, but there are barriers to identifying the extent and age of Phragmites stands. Successful restoration hinges on accurate estimations of these spatiotemporal factors, which calls for improved monitoring techniques. In order to assist efforts to combat the spread of Phragmites, I used a UNET (U-shaped encoder-decoder network architecture) to give researchers a reliable database of where Phragmites is present and at what life stage it is currently at. UNET models are free and effective, and have been instrumental in many research applications, such as the location and identification of tumors and lesions within the body. The UNET model was programmed to analyze satellite imagery from around the world and output data regarding the location and invasion stage of Phragmites, assisting management efforts and identifying new sites for research development. Because of its cosmopolitan abundance and the attention it has received, Phragmites provides an excellent representative for developing this identification method. The model has been designed in such a way that it can easily be adapted to fit a diverse array of ecosystems from around the world. This method for recognizing plant species will greatly improve global monitoring and conservation efforts.