Adaptive slope filtering for airborne Light Detection and Ranging data in urban areas based on region growing rule

Automatic ground filtering for Light Detection and Ranging data is a critical process for the creation of Digital Terrain Models. Several methods have been developed for filtering Light Detection and Ranging data and some improvements have been made but the problem has not been fully solved for the complicated landscape types and abrupt surfaces. In this paper, the region growing algorithm is introduced into the slope-based algorithm. A probabilistic function is introduced and the index of probability is used to further eliminate the pseudo ground points. A comprehensive test of the performance on nine study sites is conducted and compared with the results of seven other published methods based on the Kappa coefficients and the total errors. Overall, the slope-based and region growing algorithm performs the best in urban areas compared with other filtering methods published in terms of average Kappa value and total errors. The slope-based and region growing algorithm is adaptive to the thresholds of the slope and the filtering window, two commonly required parameters. The complexity of terrain does not significantly influence the performance of the slope-based and region growing algorithm, which allows it to be adopted in different terrains for urban areas.