## 5 Conclusions and Discussion  
This study proposes an intelligent discontinuity identification method leveraging RGB information from high-precision UAV models. The specific conclusions are described as follows:  
1. The algorithm proposed in this paper performs well in the identification of rock discontinuities and can effectively identify structural traces in complex environments and to some extent suppress the influence of interference factors such as illumination, vegetation, and color mutation. However, there is still room for improvement in missed detection, false detection, and trace continuity. Future research can further optimize the algorithm to improve its detection accuracy and robustness under complex conditions.  
Figure 6: Results of statistical characterization of discontinuities: (**a**) pole density map of discontinuities; (**b–d**): rose diagram of discontinuities in group 1, 2, 3; (**e–g**): trace length frequency diagram of discontinuities in group 1, 2, 3.  
2. All groups of discontinuities in the study slope exhibit log-normal trace length distributions dominated by short traces, with limited long-trace occurrences. The systematic spatial organization and maturity of the discontinuity network strongly imply tectonic controls, consistent with regional structural frameworks. This statistical framework enhances the efficiency of discontinuity characterization while advancing methods for rock slope hazard assessment.
3. The occurrence of rock mass discontinuities and their spatial relationship with slope surfaces give rise to two distinct types of discontinuities. One manifests as planar discontinuities approximately parallel to the slope surface, while the other presents as linear structural features formed by intersections with the slope surface, which are commonly referred to as lineation. The technical workflow proposed in this study specifically focuses on lineation that exhibits significant color contrast with slope surfaces. Regarding the identification of planar discontinuities, extensive research has been conducted by numerous scholars, such as [PERSON] et al. [26] and [PERSON] et al. [27]. Both types of discontinuities require consideration in subsequent rock slope hazard assessments. Therefore, the technical framework we propose serves as a supplement to previous research. In practical engineering applications, these two identification methodologies should be employed in combination.  
Conceptualization, H.C.; methodology, J.C.; validation, X.W., Z.Z. and J.H.; investigation, Q.S.; writing--original draft, H.C.; writing--review and editing, W.Z. and J.C.; project administration, H.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Scientific Research Project for the Transportation Power Pilot Program--Jilin Province Border Opening-Up Tourism Corridor (G331), grant number 2025 ZDGC-01.  
The datasets presented in this article are not readily available because the data are part of an ongoing study. Requests to access the datasets should be directed to [EMAIL_ADDRESS].  
The authors declare no conflicts of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} PCA & Principal component analysis \\ UAV & Unmanned aerial vehicle \\ \end{tabular}