Targeting complex geological environments characterized by high-steep cliffs, such as Danxia landforms, traditional geological modeling often relies on sparse subsurface detection data and low-precision Digital Elevation Models (DEM), making it difficult to accurately depict the complete 3D morphology of both the surface and the subsurface. To overcome this limitation, this paper introduces large-area, high-precision UAV Oblique Photogrammetry (OSGB) remote sensing data and proposes an OSGB-enhanced explicit–implicit integrated modeling framework. This method aims to bridge the “Visual-Computational” gap, where raw OSGB data possesses excellent visual fidelity but essentially consists of unstructured, non-manifold surface meshes, posing severe topological challenges for direct Boolean operations and volumetric calculations. Rather than merely applying existing algorithms, the methodological innovation lies in formulating a coupled architecture where explicit high-precision surface meshes mathematically constrain the implicit volumetric fields, bridging the distinct mathematical spaces of computer graphics and geostatistics. The approach first converts the OSGB reality model into high-quality explicit geometric constraints through topology repair and mesh optimization, combining Hermite Radial Basis Functions (HRBF) to establish a high-precision peak model. Subsequently, the Skinning Method is adopted to represent rivers and Quaternary thin layers, and a Dual Implicit Function managed by a binary tree is introduced to accurately resolve complex fault networks. Finally, within a unified tetrahedral grid space, a Boolean cutting process strictly following the geological evolutionary sequence is established. Application to the core area of Mount Danxia demonstrates that this framework successfully transforms large-area photogrammetric meshes into 3D geological models, realizing a transition from traditional DEM-constrained modeling to the integration of OSGB-derived, geometrically detailed surface constraints with deep geological attributes. Cross-section analysis indicates a high degree of consistency between the model and stratigraphic data. This study provides a universal technical paradigm for high-precision refined modeling in complex orogenic belts and special geomorphic areas.
Liu et al. (Mon,) studied this question.