TY  - JOUR
T1  - Derin Öğrenme ile Deprem Yüzey Kırıklarının Otomatik Belirlenmesi: 6 Şubat 2023 Kahramanmaraş Depremleri Örneği
TT  - Automatic Detection of Earthquake Surface Ruptures with Deep Learning: The Case of the February 6, 2023 Kahramanmaraş Earthquakes
AU  - Polat, Ali
PY  - 2025
DA  - June
Y2  - 2025
DO  - 10.24232/jmd.1650979
JF  - Jeoloji Mühendisliği Dergisi
PB  - TMMOB Jeoloji Mühendisleri Odası
WT  - DergiPark
SN  - 1016-9172
SP  - 89
EP  - 104
VL  - 49
IS  - 1
LA  - tr
AB  - Depremler dünyada en çok can ve mal kaybına neden olan afet türüdür. Bu yüzden deprem öncesi ve sonrası yapılacak çalışmalar önem kazanmaktadır. Depremler esnasında oluşan yüzey kırıklarının tespit edilmesi ve anlaşılması da depremlerin anlaşılmasında önem arz etmektedir. Bu çalışmada 02.06.2023 tarihinde Kahramanmaraş ilinde meydana gelen 7.7 ve 7.6 büyüklüğündeki depremlerde oluşmuş yüzey kırıklarının otomatik olarak tespit edilmesi amaçlanmıştır. Altlık olarak uydu görüntüleri, segmentasyon modeli olarak YOLOv8 kullanılmıştır. Uydu görüntüleri üzerinde yüzey kırıklarının gözle görülebildiği bir alan belirlenmiş ve bu alandaki kırıklar yardımı ile model eğitilmiştir. Verilerin %66 eğitim için %34 ise test için kullanılmıştır. Eğitilen modelin mAP@0.5 değeri 0.88 olarak tespit edilmiştir. YOLOv8 modeli, derin öğrenme teknikleriyle desteklenen bir yöntem olarak, bu tür görevlerde yüksek verimlilik vaat etmektedir. Bu yöntem kullanılarak deprem sonrası oluşacak yüzey kırıkları uydu görüntüleri üzerinde kolaylıkla tespit edilebilmektedir. Yöntem, araştırmacılara büyük alanlarda hızlı bir şekilde yüzey kırıklarının tespit edilmesine olanak sağlayarak arazi çalışmaları için önemli bir altlık sağlamaktadır. Bu sayede zaman ve ekonomik anlamdaki kayıplar en aza indirilmiş olacaktır.
KW  - Kahramanmaraş depremi
KW  - Derin öğrenme
KW  - Segmentasyon
KW  - YOLOv8
KW  - Yüzey kırığı
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UR  - https://doi.org/10.24232/jmd.1650979
L1  - https://dergipark.org.tr/en/download/article-file/4659504
ER  -