[1] Hui Z Y, Hu Y J, Jin S G et al. Road centerline extraction from airborne LiDAR point cloud based on hierarchical fusion and optimization[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 118, 22-36(2016).
[2] Chen F. A Study of methods for road extraction from airborne LiDAR data[D](2013).
[3] Chen Y F, Hou Y F, Xu Q et al. Li DAR points cloud filtering method based on adaptive morphological[J]. Journal of Geomatics Science and Technology, 31, 603-607, 613(2014).
[4] Li P C, Xu Q, Xing S et al. Weighted curve fitting filtering method based on full-waveform LiDAR data[J]. Geomatics and Information Science of Wuhan University, 43, 420-427(2018).
[5] Susaki J. Adaptive slope filtering of airborne LiDAR data in urban areas for digital terrain model (DTM) generation[J]. Remote Sensing, 4, 1804-1819(2012).
[6] Jin S H, Yang H H, Wang L Y. Research on slope filtering of point cloud data based on gridding LIDAR[J]. Geomatics & Spatial Information Technology, 36, 154-156(2013).
[7] Zhu L, Deng X S, Xing C B et al. Moving surface filtering algorithm based on multilevel seed point optimization[J]. Laser & Optoelectronics Progress, 57, 172801(2020).
[8] Xing C B, Deng X S, Xu K. Improved moving surface algorithm based on confidence interval estimation theory[J]. Acta Optica Sinica, 40, 0328001(2020).
[9] Zhu X X, Wang C, Xi X H et al. Hierarchical threshold adaptive for point cloud filter algorithm of moving surface fitting[J]. Acta Geodaetica et Cartographica Sinica, 47, 153-160(2018).
[10] Xu J Z, Wan YC, Lai Z L. Multi-scale method for extracting road centerlines from LIDAR datasets[J]. Infrared and Laser Engineering, 38, 1099-1103(2009).
[11] Song Y L, Hu Y. A semi-automatic extraction method of road point clouds from LiDAR data[J]. Science of Surveying and Mapping, 40, 92-94, 121(2015).
[12] Li F, Cui X M, Liu X Y et al. A semi-automatic algorithm of extracting urban road networks from airborne LiDAR point clouds[J]. Science of Surveying and Mapping, 40, 88-92(2015).
[13] Li Y, Yong B, Wu H Y et al. Road detection from airborne LiDAR point clouds adaptive for variability of intensity data[J]. Optik, 126, 4292-4298(2015).
[14] Zhang A W, Liu L L, Zhang X Z. Multi-feature 3D road point cloud semantic segmentation method based on convolutional neural network[J]. Chinese Journal of Lasers, 47, 0410001(2020).
[15] Yuan Z H, Xiao L P. Urban road extraction based on airborne LiDAR point cloud data[J]. Geomatics & Spatial Information Technology, 42, 166-169(2019).
[16] Martínez Sánchez J, Fernández Rivera F, Cabaleiro Domínguez J C et al. Automatic extraction of road points from airborne LiDAR based on bidirectional skewness balancing[J]. Remote Sensing, 12, 2025(2020).