Invasive species can cause catastrophic impacts on ecosystem health and function. Under a changing climate, urban expansion, and extreme weather events, the occurrence and impacts of invasive species is expected to increase. Remote sensing has been used as a tool to monitor the current extent and predict future spread of invasive species in aquatic and terrestrial environments. This training will identify types of remote sensing data and products that can be used for terrestrial invasive species mapping and monitoring. Participants will be introduced to airborne and in situ field data applications for invasive species mapping utilizing data sets acquired during the BioSCAPE campaign in South Africa. A demonstration of invasive species mapping using a managed Jupyterhub Python environment will provide the opportunity to apply a cloud based workflow to train airborne data from the Airborne Visible-Infrared Imaging Spectrometer Next-Generation (AVIRIS-NG) and utilize in situ field data. Participants will develop a site specific scene demonstrative of using in situ field data and imaging spectroscopy to map and visualize data, providing insights into the analysis of estimating invasive species using supervised image classification. Participants will leave with a better understanding of the applications and limitations of imaging spectroscopy and airborne data products. Participants will develop skills to apply their knowledge of the data to areas of interest to inform land management and planning decisions.