Land Use and Cover Classification of Sentinel-1A SAR Imagery: A Case Study of Istanbul

ÜSTÜNER M., Sanli F. B., BİLGİN G., Abdikan S.

25th Signal Processing and Communications Applications Conference (SIU), Antalya, Türkiye, 15 - 18 Mayıs 2017 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/siu.2017.7960373
  • Basıldığı Şehir: Antalya
  • Basıldığı Ülke: Türkiye
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

In this study, Sentinel-IA SAR imagery for land use/cover classification and its impacts on classification algorithms were addressed. Sentinel-1A imagery has dual polarization (VV and VH) and freely available from ESA. Istanbul was selected as the study region. After the pre-processing steps including the applying the precise orbit file, calibration, multilooking, speckle filtering and terrain correction, the imagery was classified as the following step. Three classification algorithms (SVM, RF and K-NN) were implemented and the impacts of additional bands (VV-VH, VV+VH etc.) were investigated. Results demonstrated that highest classification accuracy of this study was obtained by SVM classification with the original bands (VV and VH) of Sentinel-IA imagery. Moreover, it was concluded that additional bands had different impacts on each classifier within accuracy.