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Coal mining in loess plateau environment has caused serious damage to land resources and ecological environment, and it is imperative to construct a fine DEM of the mining area. In this paper, a series of point cloud construction DEM processes are investigated and discussed with respect to the various errors affecting the UAV airborne LiDAR survey system in constructing a fine digital elevation model (DEM) of the mining area under the complex terrain of the Loess Plateau. Firstly, the applicability of several mainstream point cloud filtering and point cloud interpolation algorithms in the Loess Plateau mining area is compared and analysed, and it is found that the progressive triangular mesh encrypted filtering algorithm and the inverse distance-weighted interpolation algorithm show better point cloud filter classification accuracy and interpolation accuracy for constructing DEMs in the study area. Finally, the constructed DEMs were denoised using a locally weighted regression algorithm to further reduce the noise error in the DEMs, and the feasibility of the DEM denoising method was verified by comparing the error of this process with that of the DEMs constructed using the inverse distance-weighted algorithm. This study has led to a significant improvement in the accuracy of airborne topographic survey results in loess plateau mining areas.
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