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| Titel |
UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning |
| VerfasserIn |
J. Fernandez Galarreta, N. Kerle, M. Gerke |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Sciences ; 15, no. 6 ; Nr. 15, no. 6 (2015-06-01), S.1087-1101 |
| Datensatznummer |
250119523
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| Publikation (Nr.) |
 copernicus.org/nhess-15-1087-2015.pdf |
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| Zusammenfassung |
| Structural damage assessment is critical after disasters but remains a
challenge. Many studies have explored the potential of remote sensing data,
but limitations of vertical data persist. Oblique imagery has been
identified as more useful, though the multi-angle imagery also adds a new
dimension of complexity. This paper addresses damage assessment based on
multi-perspective, overlapping, very high resolution oblique images obtained
with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the
entire building is combined with detailed object-based image analysis (OBIA)
of façades and roofs. This research focuses not on automatic damage
assessment, but on creating a methodology that supports the often ambiguous
classification of intermediate damage levels, aiming at producing
comprehensive per-building damage scores. We identify completely damaged
structures in the 3-D point cloud, and for all other cases provide the
OBIA-based damage indicators to be used as auxiliary information by damage
analysts. The results demonstrate the usability of the 3-D point-cloud data
to identify major damage features. Also the UAV-derived and OBIA-processed
oblique images are shown to be a suitable basis for the identification of
detailed damage features on façades and roofs. Finally, we also
demonstrate the possibility of aggregating the multi-perspective damage
information at building level. |
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