"Improving Ground Elevation Accuracy by Spaceborne Lidar Waveforms over Rugged Mountain Vegetated Areas"

"Received waveforms of spaceborne Light Detection and Ranging (lidar) over mountainous vegetated areas comprise multiple overlapped components. It encounters a challenge to extract the ground elevation from the complex waveform due to the difficulty in the determination of the ground return component location and the ground return extent. This study proposes an algorithm to resolve such issue, which includes: 1) based on abundant simulated lidar waveforms, we establish a regression model of the ground return extent with regard to the signal-to-noise ratio (SNR) of the received waveform and the surface slope. 2) we decompose the waveform components by the pattern matching and nonlinear least-square fitting methods, and then, 3) we extract the centroid of the decomposed waveform components within the ground return extent as the ground Elevation. Using the Global Ecosystem Dynamics Investigation (GEDI) lidar waveforms in Henry W. Coe State Park of USA, the ground elevations are resolved and compared to those by the existing methods and the GEDI products. The results demonstrate that our proposed method outperforms other methods, especially for the lower-SNR waveforms (<16 dB) with the over steep terrains (>20\u00b0). The bias, the root mean square error and the mean absolute error of the derived ground elevations by our proposed algorithm are -0.08 m, 3.33 m and 2.31 m (laser shot number is 22291), which have the reductions of 96.7 %, 30.9%, and 34.6% than the GEDI product, respectively. It indicates that our proposed algorithm can effectively improve the accuracy of the ground elevation over rugged mountainous vegetated areas.Supplementary code and processed data for reproducibility of the manuscript. Includes GEDI data, SRTM DEM, intermediate results, and processing code."