Identification of outcropping strata from UAV oblique photogrammetric data using a spatial case-based reasoning model

Abstract

Due to the large scale and complex terrain of some outcrops, it is difficult to carry out comprehensive and detailed stratum identification using traditional geological methods. The emergence of oblique photogrammetry technology provides a new way to construct high-precision 3D models of outcrops, but the existing object extraction methods of 3D models cannot be applied to the differentiation of strata in an outcrop. Therefore, this paper proposes a novel identification method for outcropping strata from oblique photogrammetric data using a spatial case-based reasoning (SCBR) model. The method includes (a) constructing point cloud of the outcrop based on the photogrammetric data; (b) segmenting the point cloud into voxels; (c) creating an integrated expression of the spatial and attribute features of a stratum case; (d) creating an integrated similarity reasoning model of the spatial and attribute features; and (e) dividing the strata after reasoning. Furthermore, this study carried out stratum identification experiments on two cases of study in Fugu, Shaanxi, China. After Performing the SCBR model, the overall accuracies were found to reach 94%. After the stratum division after reasoning was carried out, the verification accuracies were found to exceed 99%. Based on the results of the manual stratum differentiation, the differentiation results of the proposed SCBR model were found to be much more consistent with the actual situation. The experiments show that the proposed method is very effective for differentiating outcropping strata and provides a new approach for the extraction of 3D objects generated with oblique photogrammetric data.