Skip to main content
padlock icon - secure page this page is secure

Extracting buildings from and regularizing boundaries in airborne lidar data using connected operators

Buy Article:

$60.00 + tax (Refund Policy)

The location of building boundary is a crucial prerequisite for geographical condition monitoring, urban management, and building reconstruction. This paper presents a framework that employs a series of algorithms to automatically extract building footprints from airborne (light detection and ranging (lidar)) data and image. Connected operators are utilized to extract building regions from lidar data, which would not produce new contours nor change their position and have very good contour-preservation properties. First, the building candidate regions are separated from lidar-derived digital surface model (DSM) based on a new method proposed within this paper using connected operators, and trees are removed based on the normalized difference vegetation index (NDVI) value of image. Then, building boundaries are identified and building boundary lines are traced by ‘sleeve’ line simplification method. Finally, the principal directions of buildings are used to regularize the directions of building boundary lines. International Society for Photogrammetry and Remote Sensing (ISPRS) data sets in Vaihingen whose point spacing is about 0.4 m from urbanized areas were employed to test the proposed framework, and three test areas were selected. A quantitative analysis showed that the method proposed within this paper was effective and the average offset values of simple and complex building boundaries were 0.2–0.4 m and 0.3–0.6 m, respectively.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Affiliations: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

Publication date: February 16, 2016

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more