A hybrid approach to extraction and refinement of building footprints from airborne lidar data

Show simple item record

dc.identifier.uri http://dx.doi.org/10.15488/1101
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/1125
dc.contributor.author Huang, Hai
dc.contributor.author Sester, Monika
dc.date.accessioned 2017-02-03T08:18:40Z
dc.date.available 2017-02-03T08:18:40Z
dc.date.issued 2011
dc.identifier.citation Huang, Hai; Sester, Monika: A hybrid approach to extraction and refinement of building footprints from airborne lidar data. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: [Geospatial Data Infrastructure: From Data Acquisition And Updating To Smarter Services] 38-4 (2011), Nr. W25, S. 153-158. DOI: https://doi.org/10.5194/isprsarchives-XXXVIII-4-W25-153-2011
dc.description.abstract This work presents a combined bottom-up and top-down approach to extraction and refinement of building footprints from airborne LIDAR data. Building footprints are interesting for many applications in urban planning. The cadastral maps, however, may be limited for certain areas or not be updated frequently. Airborne laser scanning data is therefore considered by many people in the last decade as an important alternative data for change detection and update of building footprints. Laser scanning data of city scenes, however, often shows noise and incompleteness because of, e.g., the clutter by vegetation and the reflection of windows/waterlogged depressions on the roof. Results of the bottom-up detection may thus be limited to incomplete or irregular polygons. We employ 3D Hough transform to detect the building points. An improved joint multiple-plane detection scheme is proposed to find and label the laser points on multiple roof facets synchronously. The bottom-up processing provides not only a rough point segmentation but also additional 3D information, e.g., roof heights and horizontal ridges. Using these as priors, a top-down reconstruction is conducted via generative models. We consider the building footprint as an assembly of regular primitives. A statistical search by means of Reversible Jump Markov Chain Monte Carlo and Maximum A Posteriori estimation is implemented to find the optimal configuration of the footprint. By these means a robust and plausible reconstruction is guaranteed. First results on point clouds with various resolutions show the potential of this approach. eng
dc.description.sponsorship DFG/BR2970/2-2
dc.language.iso eng
dc.publisher Göttingen : Copernicus GmbH
dc.relation.ispartof International-Society-for-Photogrammetry-and-Remote-Sensing Guilin Workshop on Geospatial Data Infrastructure - From Data Acquisition and Updating to Smarter Services, October 20-21, 2011, Guilin, Peoples R China
dc.relation.ispartofseries International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: [Geospatial Data Infrastructure: From Data Acquisition And Updating To Smarter Services] 38-4 (2011), Nr. W25
dc.rights CC BY 3.0
dc.rights.uri https://creativecommons.org/licenses/by/3.0/
dc.subject Urban eng
dc.subject Building eng
dc.subject Extraction eng
dc.subject LIDAR eng
dc.subject Point Cloud eng
dc.subject Three-dimensional eng
dc.subject.ddc 550 | Geowissenschaften ger
dc.title A hybrid approach to extraction and refinement of building footprints from airborne lidar data
dc.type article
dc.type conferenceObject
dc.type Text
dc.relation.issn 2194-9034
dc.relation.doi https://doi.org/10.5194/isprsarchives-XXXVIII-4-W25-153-2011
dc.bibliographicCitation.issue W25
dc.bibliographicCitation.volume 38-4
dc.bibliographicCitation.firstPage 153
dc.bibliographicCitation.lastPage 158
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


Files in this item

The following license files are associated with this item:

This item appears in the following Collection(s):

Show simple item record

 

Search the repository


Browse

My Account

Usage Statistics