A Voxel-Based Skewness and Kurtosis Balancing Algorithm for Updating Road Networks from Airborne Lidar Data

In this paper, we proposed a road extraction algorithm that utilises voxel-based skewness and kurtosis balancing in order to update existing road networks accurately and reliably from airborne lidar data. The proposed algorithm consists of initial road extraction followed by a series of refinements including width constraints, spatial interpolations and curve fitting which are successfully implemented to reduce false-positives, join up misclosures and determine centrelines of the extracted roads. A numerous sample lidar datasets are tested in order to assess the proposed algorithm. The quantified completeness and correctness of the classification results are 98.20% and 98.54%, respectively; hence it is concluded that the proposed algorithm works effectively in acquisition of road features from airborne lidar data.