Abstract
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was launched on September 15, 2018. It is the first photon-counting laser altimeter satellite, which is of great significance for the research into laser altimetry. ICESat-2 is, however, highly sensitive and susceptible to environmental influences. In addition to surface returns, a lot of nonsurface photons are found in the data. It is, therefore, necessary to study an effective method to separate the surface signal from background information. In this article, we review the existing surface detection methods for photon point cloud data and select seven methods for comparison. Four sources of photon-counting data were considered in the experiments: The Multiple Altimeter Beam Experimental Lidar (MABEL), the Chinese Multibeam LiDAR, The Advanced Topographic Laser Altimeter System (ICESat-2/ATLAS), and MATLAS (using MABEL data to simulate the expected ATLAS photon point cloud). Four scenarios of land, land ice, sea ice, and ocean were also considered. Each surface detection method was tested in 12 experiments, and the different methods were finally compared by qualitative and quantitative measures. We were, thus, able to establish the advantages and disadvantages of each method, which will be of great significance for scholars studying surface detection methods.
Highlights
Laser altimetry is one of the frontiers and core technologies for spatial information acquisition in Earth observation and deep space exploration[1]
Photon-counting LiDAR (PCL) technology is likely to be the major approach used to carry out satellite laser altimetry and three-dimensional imaging in the future, and will be the main way to resolve the contradiction between LiDAR energy consumption and acquisition frequency
We focus on the surface detection methods for photon-counting LiDAR (PCL) data
Summary
Laser altimetry is one of the frontiers and core technologies for spatial information acquisition in Earth observation and deep space exploration[1]. Most of the existing Earth observation laser altimeters, such as the Ice, Cloud and Land Elevation Satellite /the Geoscience Laser Altimeter System(ICESat/GLAS), the ZiYuan-3 02 (ZY-3 02) laser altimeter, and the Gaofen 7(GF-7) laser altimeter, use linear detection systems with high-energy laser consumption. Such laser altimeters have a limited repetition frequency when collecting large-scale and multi-temporal 3D data on space platforms such as satellites, resulting in low data density [9]. The LiDAR Surface Topography (LIST) mission, the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission, and the Aerosols-Cloud-Ecosystem (ACE) mission are
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