Shape based classification of seismic building structural types

Raphael Sulzer, Pirouz Nourian, M. Palmieri, Jan van Gemert

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

4 Citations (Scopus)
79 Downloads (Pure)

Abstract

This paper investigates automatic prediction of seismic building structural types described by the Global Earthquake Model (GEM) taxonomy, by combining remote sensing, cadastral and inspection data in a supervised machine learning approach. Our focus lies on the extraction of detailed geometric information from a point cloud gained by aerial laser scanning. To describe the geometric shape of a building we apply Shape-DNA, a spectral shape descriptor based on the eigenvalues of the Laplace-Beltrami operator. In a first experiment on synthetically generated building stock we succeed in predicting the roof type of different buildings with accuracies above 80%, only relying on the Shape-DNA. The roof type of a building thereby serves as an example of a relevant feature for predicting GEM attributes, which cannot easily be identified and described by using traditional methods for shape analysis of buildings. Further research is necessary in order to explore the usability of Shape-DNA on real building data. In a second experiment we use real-world data of buildings located in the Groningen region in the Netherlands. Here we can automatically predict six GEM attributes, such as the type of lateral load resisting system, with accuracies above 75% only by taking a buildings footprint area and year of construction into account.
Original languageEnglish
Title of host publicationInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Subtitle of host publication13th 3D GeoInfo Conference 2018
EditorsK. Arroyo Ohori, A. Labetski, G. Agugiaro, M. Koeva, J. Stoter
PublisherISPRS
Pages179-186
VolumeXLII-4/W10
DOIs
Publication statusPublished - 2018
Event13th 3D GeoInfo Conference - Delft, Netherlands
Duration: 1 Oct 20182 Oct 2018
Conference number: 13
https://3dgeoinfo2018.nl/

Conference

Conference13th 3D GeoInfo Conference
Country/TerritoryNetherlands
CityDelft
Period1/10/182/10/18
Internet address

Keywords

  • Seismic Building Structural Type
  • Classification
  • Point Cloud
  • Shape Descriptor
  • Shape-DNA
  • Machine Learning

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