A two-stage algorithm for extraction of ground and top of canopy in photon-counting profiling-LiDAR data in preparation for the ICESat-2 mission

Estimating forest canopy heights over large geographical regions is important for quantifying global carbon stocks, which in turn are needed for the study of climate change. Laser altimetry (LiDAR) is increasingly popular as a sensing technique for vegetation height and structure. NASA's ICESat-2, which is scheduled for launch in July 2017, will provide a platform for collecting LiDAR-based canopy height measurements on a global scale over a two-year period. However, unlike the first ICESat mission, which utilized a waveform LiDAR, ICESat-2 will be equipped with a photon-counting LiDAR system. This new sensor is capable of providing increased accuracy in high-slope terrain, but it is also expected to produce large amounts of noise, depending on sun angle and atmospheric conditions. This paper describes recent improvements to a novel two-stage algorithm that estimates ground and canopy surfaces from photon-counting LiDAR, in preparation for the ICESat-2 mission.