DETECTION OF COLLAPSED BUILDING FROM UNMANNED AERIAL VEHICLE DATA WITH OBJECT BASED IMAGE CLASSIFICATION

Yıl 2018, Cilt: 6 Sayı: ozel, 109 - 116, 01.12.2018

Resul Çömert Dilek Küçük Matcı Uğur Avdan

Öz

Buildings are most affected the objects by earthquake disaster. Detection of collapsed buildings after an earthquake is important both for determining the current situation and quick response. Unmanned aerial vehicles that have evolved in recent years, can provide very high resolution images of the earth surface using camera systems attached to them. Information for the intended purpose can be obtained through the products produced from these images. In this study, collapsed buildings were detected in the area where high-resolution images were obtained whit unmanned aerial vehicle in 2015 and 2014. Building detection process was made based on a scenario events. In this context, 2015 images were taken before the earthquake and 2014 images were taken after the earthquake. The images of both years were processed separately to produce the digital elevation model and orthophoto image of the study area. building of the study area were obtained by applying the object-based classification process to the generated data. 11 buildings which were available in the area in 2015 and not available in the area in 2014, were detected successfully comparison of building classes of two years.

Anahtar Kelimeler

Collapsed Building, Object Based Classification, Remote Sensing, UAV

Kaynakça

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