Recent advances in forest health monitoring have focused on the use of satellite remote sensing techniques to map the year, extent, and location of forest disturbance. Although many newly developed algorithms can detect disturbance in an automated manner, many of the map products only indicate where and when a potential change has occurred. One critical piece of information that is often lacking is the causal agent responsible for the disturbance, such as fire, harvest, or insects. A recent Forest Service study found that change metrics derived from Landsat spectral trajectories can be used to accurately model different types of forest disturbance. Using a two-step modeling approach, Forest Service researchers at the agency’s Southern Research Station were able to map annual changes brought on by fire, harvesting, insects and disease, wind, and conversion of forest to other land uses. The researchers studied 10 diverse locations across the U.S. Separating forest management practices like harvests from forest land use conversion is an important advancement, because both disturbances tend to look similar in spectral space, but they have vastly different carbon consequences. In addition to testing the agent mapping approach, the researchers also offer guidance on other forest health monitoring issues. Their study addresses reference data collection, predictor variable importance, and modeling criteria. Results may impact future development of a national forest disturbance mapping product.