## 7 Conclusions  
Based on the collection and fusion of multi-source data, this paper performed intelligent identification and information extraction of the rock surface discontinuity for the high and steep cliffs on the south side of Laojun Peak in Huidong County. The study achieved good results and solved the problem of the manual inability to obtain the rock mass orientation information under special circumstances, and provided an effective reference for engineering geological investigation. Based on the extracted geometric information of rock discontinuities, a kinematic analysis model can be constructed, which can provide basic data for rock stability evaluation. The main conclusions are as follows.  
1. Ground 3D laser scanning and UAV photogrammetry technology can rapidly and efficiently obtain high-density, high-precision 3D point cloud information under complex geological environment conditions. However, both technologies have their drawbacks. The ground 3D laser scanning technology can achieve highly precise measurement with a scanning error of 2 mm-6 mm, but it is difficult to obtain complete point clouds under complex terrain environments such as those with large height differences. The UAV tilt photogrammetry technology is prone to camera distortion and blurred images, which leads to low measurement accuracy and large data errors. By adopting the unified coordinate system and improved ICP algorithm for point cloud fusion, the photogrammetric point cloud is used to supplement the missing part of the 3D laser point cloud, which not only ensures data integrity but also data accuracy. The fusion accuracy error is less than 2.8 m with a better fusion effect. This method can provide an accurate data source for the intelligent identification of discontinuous surfaces of special geological rock masses, such as high and steep cliffs, and ensures the accuracy of the identification. This is of great importance in geological investigations.
2. The spatial index is established by the Kd-tree algorithm, and the optimal scale of the adaptive neighborhood is obtained by neighborhood information entropy, which overcomes the problem of over-segmentation or under-segmentation of point clouds brought by too large or too small a neighborhood radius K, and ensures the accuracy of the point cloud normal vector and rock mass orientation calculation.
3. Based on the multi-source fusion of point clouds, we use an improved KNN search algorithm, a KDE algorithm combined with the DBSCAN algorithm, to intelligently extract rock discontinuity surface information, which provides a complete technical process and method to obtain highly precise rock mass orientation information under complex geological conditions. It helps to further analyze rock stability.  
**Author Contributions:** Conceptualization, X.K., Y.X., X.W., Z.W., K.Y., C.L., M.Y. and H.T.; methodology, X.K., Y.X., X.W., Z.W., K.Y., C.L., M.Y. and H.T.; software, X.K.; validation, X.K., Y.X., X.W., Z.W., K.Y., C.L., M.Y. and H.T.; resources, Y.X., X.W., Z.W. and K.Y.; data curation, X.K., Y.X. and Z.W.; writing--original draft preparation, X.K.; funding acquisition, Y.X., X.W., Z.W. and K.Y. All authors have read and agreed to the published version of the manuscript.  
This work was financially supported by the National Natural Science Foundation of China (No. 41861054).  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data used to support the findings of this study are available from the first author upon request.  
We thank the Second Survey Institute of Yunnan Geological Engineering for providing field geological survey information and assistance. We also thank the reviewers and editors of _the Journal of Applied Sciences_ for their hard work.  
The authors declare that they have no known competing financial interest or personal relationships that could have appeared to influence the work reported in this paper.