Knowing the surface morphology of gravel is critical for understanding the landforms and surface processes of gravel deserts. However, previous methods often relied on two-dimensional (2D) parameters, failing to capture the three-dimensional (3D) geometry and non-uniform spatial clustering of individual gravels. To address this limitation, this study presents an innovative 3D characterization and reconstruction approach for desert gravels. Through the combination of Structure from Motion (SfM) photogrammetry, spatial clustering, and statistical fitting, high-precision 3D morphological and spatial distribution parameters were successfully extracted from typical gravel deserts. Crucially, through the integration of these statistical characteristics and natural randomness, a novel gravel surface reconstruction software (Gravel 3D) was developed. This software can automatically generate arbitrary, realistic artificial 3D gravel surfaces. This approach provides realistic aerodynamic boundary simulations of different gravel surfaces on Earth and even Mars.
Zhou et al. (Sat,) studied this question.