Selective logging is a common commercial activity in tropical forests where only a few valuable tree species are harvested. The spatial extent of logging and duration of logging impacts are highly uncertain because much of the activity is illegal and because remote sensing methods for logging detection have not been automated successfully. USDA Forest Service scientists employed airborne laser scanning, or LiDAR, in 2012 and 2014 to estimate three-dimensional changes in the forest canopy and understory structure following reduced-impact selective logging on a site in the Eastern Amazon. Using the LiDAR data from 2012 only, they developed a novel statistical technique to identify logging that occurred up to eight years prior to that date. They then tested the technique using only 2014 data to detect new logging that occurred between the 2012 and 2014 data acquisitions. Their technique accurately identified the new logging areas and assigned confidence for each detection at a spatial resolution of about 3 hectares (about 7 acres). Logging is damaging vast areas of tropical forests, but the extent and intensity of the damage is unknown. Tropical forests harbor biodiversity and regulate climate. Logging, especially illegal activities, can lead to long term and possibly irreversible damage to tropical forests. Currently, monitoring logging is expensive and it can be dangerous for enforcement agents on the ground. The ability to monitor logging using remotely sensed data and automated approaches reduces costs and is a first step to effective control. A government cannot regulate what it cannot measure.