Building boundary extraction from airborne lidar point clouds

Hsiao Chu Hung, Cheng Kai Wang, Yi Hsing Tseng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Building boundaries are important spatial features that characterize the topographic maps and three-dimensional (3D) city models. Airborne LiDAR Point clouds provide adequate 3D spatial information for building boundary mapping. However, information of boundary features contained in point clouds is implicit. This study focuses on developing an automatic algorithm of building boundary extraction from airborne LiDAR data. Usually top surfaces, such as roofs, may have densely distributed points, but vertical surfaces, such as walls, usually have sparsely distributed points or even no points. The intersections of roof and wall planes are, therefore, not clearly defined in point clouds. Therefore two major process steps are presented in the algorithm to improve the edge extraction from LiDAR data. The first step is to extract building boundary points from point clouds, and then the second step is to form building boundary line features based on the extracted boundary points. The test data in our experiments include a variety of buildings. The experiment results show the effectiveness of the proposed method for automatic building boundary extraction from airborne LiDAR data, and that combining the information of the first and intermediate echo points of multi-return and the boundary points increases the completeness of boundaries. And, it is promising to use the extracted boundaries for 3D building modelling in the future.

Original languageEnglish
Title of host publication34th Asian Conference on Remote Sensing 2013, ACRS 2013
PublisherAsian Association on Remote Sensing
Pages807-814
Number of pages8
ISBN (Print)9781629939100
Publication statusPublished - 2013 Jan 1
Event34th Asian Conference on Remote Sensing 2013, ACRS 2013 - Bali, Indonesia
Duration: 2013 Oct 202013 Oct 24

Publication series

Name34th Asian Conference on Remote Sensing 2013, ACRS 2013
Volume1

Other

Other34th Asian Conference on Remote Sensing 2013, ACRS 2013
CountryIndonesia
CityBali
Period13-10-2013-10-24

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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