Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 347-350, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-347-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
21 Jun 2016
PRELIMINARY RESULTS OF EARTHQUAKE-INDUCED BUILDING DAMAGE DETECTION WITH OBJECT-BASED IMAGE CLASSIFICATION
A. Sabuncu1,3, Z. D. Uca Avci2, and F. Sunar3 1Bogazici University, Kandilli Observatory and Earthquake Research Institute Geodesy Department, Istanbul, Turkey
2Istanbul Technical University, Department of Astronautical Engineering, Faculty of Aeronautics and Astronautics, Istanbul, Turkey
3Istanbul Technical University, Geomatics Engineering Department, Istanbul, Turkey
Keywords: Ercis-Van Earthquake, Object-Based Image Classification, Building Damage Detection Abstract. Earthquakes are the most destructive natural disasters, which result in massive loss of life, infrastructure damages and financial losses. Earthquake-induced building damage detection is a very important step after earthquakes since earthquake-induced building damage is one of the most critical threats to cities and countries in terms of the area of damage, rate of collapsed buildings, the damage grade near the epicenters and also building damage types for all constructions. Van-Ercis (Turkey) earthquake (Mw= 7.1) was occurred on October 23th, 2011; at 10:41 UTC (13:41 local time) centered at 38.75 N 43.36 E that places the epicenter about 30 kilometers northern part of the city of Van. It is recorded that, 604 people died and approximately 4000 buildings collapsed or seriously damaged by the earthquake.

In this study, high-resolution satellite images of Van-Ercis, acquired by Quickbird-2 (© Digital Globe Inc.) after the earthquake, were used to detect the debris areas using an object-based image classification. Two different land surfaces, having homogeneous and heterogeneous land covers, were selected as case study areas. As a first step of the object-based image processing, segmentation was applied with a convenient scale parameter and homogeneity criterion parameters. As a next step, condition based classification was used. In the final step of this preliminary study, outputs were compared with streetview/ortophotos for the verification and evaluation of the classification accuracy.

Conference paper (PDF, 1553 KB)


Citation: Sabuncu, A., Uca Avci, Z. D., and Sunar, F.: PRELIMINARY RESULTS OF EARTHQUAKE-INDUCED BUILDING DAMAGE DETECTION WITH OBJECT-BASED IMAGE CLASSIFICATION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 347-350, https://doi.org/10.5194/isprs-archives-XLI-B7-347-2016, 2016.

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