Automated extraction of building geometry from mobile laser scanning data collected in residential environments

Alireza G. Kashani, Andrew J. Graettinger, David Grau

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

2 Scopus citations

Abstract

Spatial data collection in urban environments for the extraction of building inventory information is important for many applications, such as urban planning, storm water management, hazard mitigation, vulnerability assessment, and loss estimation, to name a few. Creating and updating building inventory databases in large and developing urban environments benefits from efficient data acquisition and data processing techniques. This study leveraged and integrated the advantages of ground-based mobile laser scanning and aerial photography through an automated method to extract building inventory information. The integration of terrestrial and aerial data enables the identification of buildings in the data set and the extraction of both roof polygons and wall footprints. The presented method was evaluated with actual data sets collected from a typical residential area. The area of roof polygons extracted by the automated approach differs by less than 5% when compared to manually calculated values. Also, the proposed method allows for accurate extraction of walls captured within the point cloud.

Original languageEnglish (US)
Title of host publicationConstruction Research Congress 2014
Subtitle of host publicationConstruction in a Global Network - Proceedings of the 2014 Construction Research Congress
PublisherAmerican Society of Civil Engineers (ASCE)
Pages955-963
Number of pages9
ISBN (Print)9780784413517
DOIs
StatePublished - Jan 1 2014
Event2014 Construction Research Congress: Construction in a Global Network, CRC 2014 - Atlanta, GA, United States
Duration: May 19 2014May 21 2014

Publication series

NameConstruction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress

Other

Other2014 Construction Research Congress: Construction in a Global Network, CRC 2014
CountryUnited States
CityAtlanta, GA
Period5/19/145/21/14

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ASJC Scopus subject areas

  • Building and Construction

Cite this

Kashani, A. G., Graettinger, A. J., & Grau, D. (2014). Automated extraction of building geometry from mobile laser scanning data collected in residential environments. In Construction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress (pp. 955-963). (Construction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress). American Society of Civil Engineers (ASCE). https://doi.org/10.1061/9780784413517.0098