Effective forest management requires understanding where forest productivity may be affected by climatic events like hurricanes or drought. Detecting these changes in satellite imagery, however, requires long-term seasonal image data. In persistently cloudy tropical regions like Puerto Rico and the U.S. Virgin Islands, deriving long-term trends from satellite imagery is challenging. Vegetation seasonality is complicated by steep topography and the small number of times any one place is imaged when the sky is also clear. USDA Forest Service scientists and collaborators are developing a long-term dataset of forest greenness that will track seasonal patterns of greenness, which are related to forest productivity, for the years 2000 through 2018. By refining algorithms that they previously developed and applied, they hope to detect seasonal vegetation greenness, even where there is more frequent cloud cover and steeper topography than in previous tests. They will use these data in conjunction with data from the Forest Inventory and Analysis program to characterize the changes in forest productivity related to recent drought and hurricanes.