In April of 2019 UMD GLAD team members Matthew Hansen, Andres Hernandez and Jeffrey Pickering took a Riegl LiDAR drone to the Republic of Congo to experiment with acquiring and processing LiDAR data. Currently GLAD employs a combination of mapping and sampling to estimate areas of forest loss for different countries in collaboration with national partners. However, quantifying changes in biomass associated with forest disturbances requires accurate measurements of forest structure. The goal of the field visit to the Republic of Congo was to acquire LiDAR measurements of forest structure for a sample of locations identified as disturbed in Landsat-based forest change maps. Forest disturbances in the Republic of Congo are mostly associated with industrial selective logging.