Analysis of the influence of different algorithms of GEDI L2A on the accuracy of ground elevation and forest canopy height

doi:10.7523/j.ucas.2021.0076

Abstract

Abstract: The global ecosystem dynamics investigation(GEDI) is a full-waveform LiDAR system launched by United States in December 2018, which can provide data support for global ground elevation and forest canopy height. In order to adapt to different surface environments, GEDI L2A products provide 6 different algorithms to estimate ground elevation and forest canopy height. The choice of these algorithms will affect the extraction accuracy of surface parameters. In this paper, the digital terrain model and canopy height model obtained by airborne laser scanning data are used as reference data to evaluate the adaptability of different algorithms of the second version of GEDI L2A data under different vegetation coverage values and the impact on the accuracy of ground elevation and forest canopy height. The results show that when the vegetation coverage is less than 0. 2, the result of algorithm 4 is the best, when the coverage is greater than or equal to 0. 8, the result of algorithm 2 is the best, and the result of algorithm 1 is the best under the remaining coverage values. Comparing the optimal algorithm selected in this paper according to the vegetation coverage with the GEDI L2A default optimal algorithm, the results of this paper are generally better than those of the GEDI L2A default optimal algorithm, especially when the coverage value is less than 0. 8 and the slope is greater than or equal to 10°. The optimal algorithm selected in this paper can effectively improve the accuracy of GEDI L2A products for estimating ground elevation and forest canopy height.

Key words: GEDI, full waveform LiDAR, ground elevation, forest canopy height

CLC Number:

P228.3

LIU Lijuan, WANG Cheng, NIE Sheng, ZHU Xiaoxiao, XI Xiaohuan, WANG Jinliang. Analysis of the influence of different algorithms of GEDI L2A on the accuracy of ground elevation and forest canopy height[J]. Journal of University of Chinese Academy of Sciences, 2022, 39(4): 502-511.

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