ICESat-2 derived canopy covers with radiometric and reflectance ratio corrections

The canopy cover is a fundamental parameter in forest inventory. The launch of Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) that carries the Advanced Topographic Laser Altimeter System (ATLAS) photon-counting lidar provides an astonishing opportunity to assess canopy covers at a large scale. Currently, the canopy covers were calculated as the proportion of vegetation photons to total signal photons using ICESat-2/ATLAS data without considering the radiometric distortion caused by photon-counting detectors and the surface reflectance of vegetation and ground. The overall goal of this study is to investigate a method to derive more accurate canopy covers considering the radiometric correction and surface reflectance correction with ICESat-2 photon data. With focusing on two study areas, Slaughter (SLAU) and Lenoir Landing (LENO) in USA, the specific purposes are to: (1) propose a radiometric correction model based on the lidar equation and response mechanism of photon-counting detectors to recover accurate vegetation and ground photons; (2) estimate the reflectance ratio between vegetation and ground according to the vegetation radiative transfer model and the density of spatial cluster method; (3) derive original and compensated canopy covers with ICESat-2 classified photons; (4) evaluate the accuracy of derived canopy covers relative to local airborne reference canopy covers; and (5) explore the effects of undergrowth vegetation and land cover types on the canopy covers. The coefficients of correlation (R) and root mean square errors (RMSE) of the compensated canopy covers are 0.86, 0.15 at SLAU and 0.59, 0.16 at LENO, compared with those for original canopy covers with 0.71, 0.18, and 0.45, 0.21, respectively. As the undergrowth vegetation and diverse land cover types have an impact on the retrieval accuracy of canopy covers, we can employ the photons of different species to obtain their specific the reflectance ratios to achieve a higher precision.