RT Journal Article
T1 Automatic Extraction of Road Points from Airborne LiDAR Based on Bidirectional Skewness Balancing
A1 Martínez Sánchez, Jorge
A1 Fernández Rivera, Francisco
A1 Cabaleiro Domínguez, José Carlos
A1 López Vilariño, David
A1 Fernández Pena, Anselmo Tomás
K1 Airbone LiDAR point clouds
K1 Road point extraction
K1 Bidirectional skewness balancing
AB Road extraction from Light Detection and Ranging (LiDAR) has become a hot topic over recent years. Nevertheless, it is still challenging to perform this task in a fully automatic way. Experiments are often carried out over small datasets with a focus on urban areas and it is unclear how these methods perform in less urbanized sites. Furthermore, some methods require the manual input of critical parameters, such as an intensity threshold. Aiming to address these issues, this paper proposes a method for the automatic extraction of road points suitable for different landscapes. Road points are identified using pipeline filtering based on a set of constraints defined on the intensity, curvature, local density, and area. We focus especially on the intensity constraint, as it is the key factor to distinguish between road and ground points. The optimal intensity threshold is established automatically by an improved version of the skewness balancing algorithm. Evaluation was conducted on ten study sites with different degrees of urbanization. Road points were successfully extracted in all of them with an overall completeness of 93%, a correctness of 83%, and a quality of 78%. These results are competitive with the state-of-the-art
PB MDPI
YR 2020
FD 2020
LK http://hdl.handle.net/10347/23451
UL http://hdl.handle.net/10347/23451
LA eng
NO Martínez Sánchez, J.; Fernández Rivera, F.; Cabaleiro Domínguez, J.C.; López Vilariño, D.; Fernández Pena, T. Automatic Extraction of Road Points from Airborne LiDAR Based on Bidirectional Skewness Balancing. Remote Sens. 2020, 12, 2025
NO This work has received financial support from the Consellería de Cultura, Educación e Ordenación Universitaria (accreditation 2019-2022 ED431G-2019/04 and reference competitive group 2019-2021, ED431C 2018/19) and the European Regional Development Fund (ERDF), which acknowledges the CiTIUS-Research Center in Intelligent Technologies of the University of Santiago de Compostela as a Research Center of the Galician University System. This work was also supported in part by Babcock International Group PLC (Civil UAVs Initiative Fund of Xunta de Galicia) and the Ministry of Education, Culture and Sport, Government of Spain (Grant Number TIN2016-76373-P)
DS Minerva
RD 24 abr 2026