The ATL08 land and vegetation product for the ICESat-2 Mission

After being launched in September 2018, measurements from the ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) will be available to the science community starting in the Spring of 2019. These data offer new possibilities for the mapping of global terrain and vegetation as well as monitoring of the Earth's carbon stocks. The Advanced Topographic Laser Altimeter System (ATLAS) instrument on-board ICESat-2 will utilize photon counting technology for the altimetry observations. Photon counting technology is relatively new to the vegetation mapping community thus requires development of new algorithm approaches for terrain surface and canopy height retrievals. Photon counting systems provide range measurements for individual photons given the instrument's detection sensitivity. The sensitivity enables higher laser repetition rates for improved spatial coverage but is susceptible to solar background noise making the separation of signal and noise challenging and the data volume large. The algorithm developed specifically for the extraction of terrain and canopy heights from the ATLAS point clouds produces the ATL08 geophysical data product. This paper provides a detailed description of the ATL08 methodology, presents the data format, discusses many of the critical parameters likely to be of interest to future ICESat-2 data users, and describes the predicated uncertainties for terrain and canopy heights using two simulated ATLAS data sets. The first critical function in the ATL08 algorithm needs to accurately retrieve the surface is to identify the signal photons apart from the noise photons. Using a series of iterative filters, the ground and top of canopy surfaces are then identified in the signal. Next, individual photons are classified as either noise, canopy, or ground photons based on their distance above (or below) the estimated ground and top of canopy surfaces. The ATL08 algorithm has been tested on several simulated ATLAS data sets, and the results from two different ecosystems are described. The terrain extraction results saw sub-meter RMSE for the Alaska Tundra/Taiga ecotone and < 2 m RMSE in Sonoma County, California which is characterized by complex topography and dense vegetation. Although canopy heights on the ATL08 data product will underestimate the true canopy height within a segment, the ICESat-2 derived canopy height is found to be correlated with relative height metrics produced from airborne lidar (i.e. truth). For the sparse boreal forests of Alaska, the ATL08 canopy height was most correlated with the 95th percentile relative height (RH95). However, for the dense coniferous forests of Sonoma County, CA, ATL08 canopy height is correlated with 75th percentile relative height (RH75). Data from ICESat-2 will provide a new and exciting data set to the scientific community by providing global terrain and canopy height estimates as well as showing potential for estimation of forest biomass.