Reconstructing DEM using TLS point cloud data and NURBS surface

Abstract

Underground coal mining inevitably results in land surface subsidence. Acquiring information on land surface subsidence is important in the detection of surface change. However, conventional data acquisition techniques cannot always retrieve information on whole subsidence area. This study focuses on the reconstruction of a digital elevation model (DEM) with terrestrial laser scanning (TLS) point cloud data. Firstly, the methodology of the DEM with terrestrial 3-dimensional laser scanning is introduced. Then, a DEM modeling approach that involves the application of curved non-uniform rational B-splines (NURBS) surface is put forward. Finally, the performance of the DEM modeling approach with different surface inverse methods is demonstrated. The results indicate that the DEM based on the point cloud data and curved NURBS surface can achieve satisfactory accuracy. In addition, the performance of the hyperbolic paraboloid appears to be better than that of the elliptic paraboloid. The reconstructed DEM is continuous and can easily be integrated into other programs. Such features are of great importance in monitoring dynamic ground surface subsidence.