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Assessment of Seismic Building Vulnerability from Space

Geiß, Christian and Taubenböck, Hannes and Tyagunov, Sergey and Tisch, Anita and Post, Joachim and Lakes, Tobia (2014) Assessment of Seismic Building Vulnerability from Space. Earthquake Spectra, 30 (4), pp. 1553-1583. Earthquake Engineering Research Institute. ISSN 8755-2930.

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This paper quantitatively evaluates the suitability of multi-sensor remote sensing to assess the seismic vulnerability of buildings for the example city of Padang, Indonesia. Features are derived from remote sensing data to characterize the urban environment and are subsequently combined with in situ observations. Machine learning approaches are deployed in a sequential way to identify meaningful sets of features that are suitable to predict seismic vulnerability levels of buildings. When assessing the vulnerability level according to a scoring method, the overall mean absolute percentage error is 10.6%, if using a supervised support vector regression approach. When predicting EMS-98 classes, the results show an overall accuracy of 65.4% and a kappa statistic of 0.36, if using a naive Bayes learning scheme. This study shows potential for a rapid screening assessment of large areas that should be explored further in the future.

Item URL in elib:https://elib.dlr.de/94593/
Document Type:Article
Title:Assessment of Seismic Building Vulnerability from Space
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Geiß, Christianchristian.geiss (at) dlr.deUNSPECIFIED
Taubenböck, Hanneshannes.taubenboeck (at) dlr.deUNSPECIFIED
Tyagunov, Sergeysergey.tyagunov (at) gfz-potsdam.deUNSPECIFIED
Tisch, Anitaanita.tisch (at) iab.deUNSPECIFIED
Post, Joachimjoachim.post (at) dlr.deUNSPECIFIED
Lakes, Tobiatobia.lakes (at) geo.hu-berlin.deUNSPECIFIED
Date:November 2014
Journal or Publication Title:Earthquake Spectra
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
Page Range:pp. 1553-1583
Publisher:Earthquake Engineering Research Institute
Keywords:Building Vulnerability, Earth Observation, Supervised Regression and Classification,
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben Zivile Kriseninformation und Georisiken (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Geiß, Christian
Deposited On:14 Jan 2015 09:22
Last Modified:03 Jun 2020 10:52

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