Sea Surface Signal Extraction for Photon-Counting LiDAR Data: A General Method by Dual-Signal Unmixing Parameters

Abstract

The ice, cloud, and land elevation satellite-2 (ICESat-2) is the only satellite that produces photon-counting light detection and ranging data, and is equipped with the advanced topographic laser altimeter system. ICESat-2 provides sea surface height product; however, its approach of the product is unsuitable for areas with sub-surface signals. Conventional denoising methods applied to sea surface photon data of variable density involve the use of different empirical parameters. Considering the distribution of sea surface signal photons, we propose a general open-source method using a dual-signal unmixing parameter (DSUMP), which incorporates the Gaussian distribution of dual-signal peaks to determine the sea surface range. This method facilitates the direct extraction of sea surface photons under various observation conditions—day or night, strong or weak beams, and including or excluding seabed photons—without requiring any variable parameters. The elevation error by DSUMP within 0.1m accounts for more than 97%. The mean absolute error is within 0.01 m compared to sea surface photons obtained via manual extraction. Different model parameters show stable denoising accuracy, only affects operating efficiency. The proposed method introduces a novel denoising technique for extracting sea surface elevation from ICESat-2 altimetry data, and its applicability can be extended to various point cloud data with similar distributions.

Keywords

• Gaussian mixture model
• ICESat-2
• photon-counting light detection and ranging (LiDAR)
• point cloud denoising
• sea surface height