BATTLE DAMAGE ASSESSMENT BASED ON SELF-SIMILARITY AND CONTEXTUAL MODELING OF BUILDINGS IN DENSE URBAN AREAS

KAHRAMAN F., Imamoglu M., Ates H. F.

36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, Çin, 10 - 15 Temmuz 2016, ss.5161-5164, (Tam Metin Bildiri) identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/igarss.2016.7730345
  • Basıldığı Şehir: Beijing
  • Basıldığı Ülke: Çin
  • Sayfa Sayıları: ss.5161-5164
  • Dokuz Eylül Üniversitesi Adresli: Hayır

Özet

Assessment of battle damages is significant both for tactical planning and for after-war relief efforts. In this study damaged buildings are detected using self-similarity descriptor in pre-and post-war satellite images. Detection accuracy is improved by the use of a contextual model that describes the building neighborhoods. Building footprints are utilized for accurate assessment of building-level changes and for the formation of neighborhood context. The Gaza Strip after 2014 Israel-Palestine conflict is analyzed with the suggested method and 84% true positive rate and 19% false positive rate are obtained on the average for detection of damaged buildings with respect to the ground truth data of UNOSAT.