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, Turkey, 15 - 18 May 2017 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2017.7960373
  • City: Antalya
  • Country: Turkey


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.