Abstract: Roads play an indispensable role as part of the infrastructure of society. In recent years, society has witnessed the rapid development of laser mobile mapping systems (LMMS) which, at high measurement rates, acquire dense and accurate point cloud data. This paper presents a way to automatically estimate the required excavation volume when widening a road from point cloud data acquired by an LMMS. Firstly, the input point cloud is down-sampled to a uniform grid and outliers are removed. For each of the resulting grid points, both on and off the road, the local surface normal and 2D slope are estimated. Normals and slopes are consecutively used to separate road from off-road points which enables the estimation of the road centerline and road boundaries. In the final step, the left and right side of the road points are sliced in 1-m slices up to a distance of 4 m, perpendicular to the roadside. Determining and summing each sliced volume enables the estimation of the required excavation for a widening of the road on the left or on the right side. The procedure, including a quality analysis, is demonstrated on a stretch of a mountain road that is approximately 132 m long as sampled by a Lynx LMMS. The results in this particular case show that the required excavation volume on the left side is 8% more than that on the right side. In addition, the error in the results is assessed in two ways. First, by adding up estimated local errors, and second, by comparing results from two different datasets sampling the same piece of road both acquired by the Lynx LMMS. Results of both approaches indicate that the error in the estimated volume is below 4%. The proposed method is relatively easy to implement and runs smoothly on a desktop PC. The whole workflow of the LMMS data acquisition and subsequent volume computation can be completed in one or two days and provides road engineers with much more detail than traditional single-point surveying methods such as Total Station or GPS profiling. A drawback is that an LMMS system can only sample what is within the view of the system from the road.
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Wang, J.; González-Jorge, H.; Lindenbergh, R.; Arias-Sánchez, P.; Menenti, M. Automatic Estimation of Excavation Volume from Laser Mobile Mapping Data for Mountain Road Widening. Remote Sens. 2013, 5, 4629-4651.
Wang J, González-Jorge H, Lindenbergh R, Arias-Sánchez P, Menenti M. Automatic Estimation of Excavation Volume from Laser Mobile Mapping Data for Mountain Road Widening. Remote Sensing. 2013; 5(9):4629-4651.
Wang, Jinhu; González-Jorge, Higinio; Lindenbergh, Roderik; Arias-Sánchez, Pedro; Menenti, Massimo. 2013. "Automatic Estimation of Excavation Volume from Laser Mobile Mapping Data for Mountain Road Widening." Remote Sens. 5, no. 9: 4629-4651.