A Gradient-constrained Morphological Operation for Retrieving Sub-canopy Topography over Densely Forested Areas from ICESat-2/ATL03 Data

The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) has been widely used to obtain high-precision sub-canopy topography. However, due to the vegetation cover over densely forested areas, the ground photons are sparse, which makes it difficult to accurately estimate the sub-canopy topography over densely forested areas. In this paper, we proposed a novel method for retrieving sub-canopy topography over densely forested areas from ICESat-2/ATL03 data. First, the proposed method used an improved elevation frequency histogram statistics (imEFHS) method to obtain candidate ground seed photons (GSPs). In densely forested areas, the obtained candidate GSPs are easily misclassified as canopy photons. Therefore, we performed a gradient-constrained morphological operation to identify erroneous GSPs. Finally, an erroneous GSPs refinement approach was derived to correct erroneous GSPs over densely forested areas. In addition, the sub-canopy topography can be presented by the refined GSPs with cubic spline interpolation. ICESat-2/ATL03 data acquired over densely forested areas were selected for testing the proposed method. The results in the given test sites show that the proposed method can extract sub-canopy topography accurately, with a root-mean-square error (RMSE) of 1.71 m over densely forested areas. We also compared the retrieved sub-canopy topography results with NASA ATL08 terrain samples. We found that the ratio of useful sub-canopy topography results (Residual < 2.5 m.) in the forest-intensive area was 87%. However, the ratio of useful ATL08 terrain samples was only 9%, which is lower than that of retrieved sub-canopy topography results. In addition, in densely forested areas, the correlation (R 2 ) between the retrieved sub-canopy topography results and the reference high-precision DTMs reached 0.93, which is much higher than that of the ATL08 terrain samples (R 2 = 0.63).