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The monitoring of highwall slopes at open-pit mines is an important task to ensure safe mining. For this reason, several techniques such as total station, radar, terrestrial Light Detection and Ranging (LIDAR) can be employed for surface measurement. The objective of this study is to investigate mesh algorithms, which can be used to interpolate 3D models of pit walls. Experiments were carried out at Coc Sau open-pit mine at Quang Ninh province of Vietnam, and at experimental mine of Akademia Górniczo-Hutnicza University of Science and Technology in Cracow, Poland. First, 3D point cloud data for the study area was acquired by using terrestrial LIDAR, then was used to generate mesh surfaces using three algorithms-Delaunay 2.5D XY Plane, Delaunay 2.5D Best Fitting Plane, and Mesh from Points. After that, the results were rectified and optimized. Subsequently, the optimized meshes were used for generation of non-uniform rational basis spline (NURBS) surfaces. Then, the NURBS surface accuracy was assessed. The results showed that the average distance between surface and point cloud was within range of 5.6-5.8 mm with deviation of 6.2-6.8 mm, depending on the used mesh. Additionally, the quality of surfaces depends on the quality of input data set and the algorithm used to generate mesh network, and the accuracy of computed NURBS surfaces fitting into pointset was 4-5 times lower than that of optimized mesh fitting. However, the accuracy of the final product allows determining displacements on the level of centimeters.

Using photo data of unmanned aerial vehicle (UAV) for building 3D models has been widely used in recent years. However, building a 3D model for deep open - pit coal mines with the mean height difference between surface and bottom of mines to over 500 m, there has not been researched mentioned. The paper deals with the assessment possibility of developing 3D models for deep open - pit mines from UAV image data. To accomplish this goal, DJI's Inspire 2 flying device is used to take the photo at Coc Sau coal mine. The flying area is 4 km2, the flight altitude compared to the takeoff point on the mine surface is 250 m, the overlaying coverage is both horizontal and vertical is 70%. The average errors of the horizontal and height elements of the reference points photo correlates are 0.011 m, 0.017 m, 0.016 m, 0.049 m, and 0.051 m. The maximum error on the X-axis is - 0,025 m, and the Y-axis is 0.028 m, the maximum horizontal error is 0.034 m, the maximum error on the Z-axis is 0.095 m, and the position error is 0.095 m. These results show that the 3D model established from photographic data by Inspire 2 device has satisfied the requirements of the accuracy of establishing the mining terrain map 1: 1000 scale.

GNSS technology has made great contributions to the development of surveying and mapping in Vietnam. Many useful GNSS processing software packages have been created and widely used all over the world. However, since these software programs only have input and output, the new users without expert theoretical knowledge (especially new students) can not understand the principle or interfere with the process to obtain explicit results at each step. Therefore, the research team has built the GNSS-HUMGAdj software package to visually illustrate GNSS data processing steps for students to use. In the design stage, the group has learnt the experience in programming GNSS processing software, inheriting published GNSS data processing algorithms. In addition, some algorithms such as converted GNSS baseline in resolving the relative positioning problem, adjusting the receiver antenna height, and the effect caused by the change of distance over time were developed in the software.

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