Credibility of 3D Volume Computation Using GIS for Pit Excavation and Roadway Constructions | Science Publications

American Journal of Engineering and Applied Sciences

Ragab Khalil¹ 

关键词: 3D Volume;    GIS;    Grid;    TIN;    Interpolation;    Average End Area;   

DOI  :  10.3844/ajeassp.2015.434.442

学科分类：工程和技术（综合）

来源: Science Publications

【 摘 要 】

Volume estimation and earthworks calculation of borrow pits and roadway constructions are typical applications in civil Engineering. Although several methods for volume estimation were introduced, the average end area method still the common method used by owners and contractors. Average end area method is tedious and time consuming. Volume of terrains that do not have regular geometric structure can be obtained more accurately by using 3D models of surfaces with respect to developing technology such as GIS. The gridding method and point distribution are important factors in modeling earth surfaces used for volume estimation. In this study the credibility of 3D volume estimation based on raster GRID or Triangular Irregular Network (TIN) using GIS was investigated. The effects of interpolation method and point distribution in defining a terrain surface were also investigated. For this purpose, an artificial surface with a known volume that used by Chen and Lin in their paper is employed. The 3D surface and volume are calculated for both surfaces represented by TIN and GRIDs generated by using 6 different interpolation methods. The resultant volumes were compared to the exact volume and to that estimated by using average end area method. Moreover a comparison between cut and fill volumes needed for grading the study cases at a certain elevation was done. The results show that for gentle slope surface, TIN and all interpolation techniques gave results very close to the exact except Kriging and Trend interpolation. For steep slope terrain, Kriging interpolation gave the best results. Comparing earthwork volume to the average end area method, TIN surface, IDW, Topo to raster and Nearest Neighbor methods gave the best results.

【 授权许可】

Unknown