A method for main road extraction from airborne LiDAR data in urban area

Author

Jiangui, Peng ; Guang, Gao

Author_Institution

Sch. of Remote Sensing & Inf. Eng., Wuhan Univ., Wuhan, China

fYear

2011

fDate

9-11 Sept. 2011

Firstpage

2425

Lastpage

2428

Abstract

A method for the automatic main road extraction in urban area from airborne LiDAR (Light Detection And Ranging) data is proposed. Elevation and intensity information are used to classify road points from the raw airborne LiDAR point clouds. Firstly, the adaptive TIN (Triangulated Irregular Network) model filtering algorithm is utilized to classify the LiDAR point clouds into ground and non-ground point clouds. Secondly, the ground point clouds are classified into candidate road and non-road point clouds by intensity information. Lastly, the constrained Delaunay TIN of candidate road point clouds is constructed to improve the accuracy of classification and then the road contour is extracted from the road points image. Experimental results show that the method can extract the main road of urban area effectively.

Keywords

airborne radar; feature extraction; filtering theory; image classification; optical radar; radar imaging; roads; Delaunay TIN; airborne LiDAR point clouds; filtering algorithm; intensity information; light detection and ranging; main road extraction; non-road point clouds; road contour; road points classification; triangulated irregular network model; Data mining; Filtering algorithms; Laser radar; Remote sensing; Roads; Tin; Urban areas; Airborne LiDAR; constrained Delaunay TIN(CD-TIN); intensity; point clouds; road;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Communications and Control (ICECC), 2011 International Conference on

Conference_Location

Ningbo

Print_ISBN

978-1-4577-0320-1

Type

conf

DOI

10.1109/ICECC.2011.6066443

Filename

6066443