Ranging Bias Correction of Fully Saturated Data Over Waters for ICESat-2 Photon-Counting Lidar

The recent capabilities of the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) photon counting lidar in monitoring water levels have been demonstrated through its precise elevation measurement and small footprint. The accuracy in water level measurements is, however, significantly impacted by the first photon bias, especially when photon-counting detectors are fully saturated due to particular reflections from calm water surfaces. In this study, we propose an analytical model to correct the first photon bias in scenarios where the ICESat-2/Advanced Topographic Altimeter System (ATLAS) is fully saturated. Notably, the model innovatively recovers and estimates the required signal level using after-pulses, which are typically considered as noise. These after-pulses can be used to effectively estimate the signal level when the detector is fully saturated. The experiment analysis, conducted on eight ICESat-2 ground tracks over calm water surfaces near the Great Lakes and the Tibetan Plateau, indicates that the actual received signal photons can surpass 200 and in some cases, reach up to 600 counts for strong beams, introducing a first photon bias exceeding 15 cm. The findings prove that 1) after-pulses can be used to retrieve water surface elevation and reflectance when the primary surface return is distorted by detector saturation and 2) calm waters reflect 5–40 times more than ice and snow surfaces, where first photon bias is a predominant error in water level measurements. The method holds great significance for the accurate monitoring of water levels in small inland water bodies using ICESat-2 and may also inform the design of lidar systems for inland water observations.