Land Use and Cover Classification of Sentinel-1A SAR Imagery: A Case Study of Istanbul
Mustafa Ustuner, Fusun Balik Sanli, Gokhan Bilgin, Saygin Abdikan, None None
proceeding (Uluslararası, Hakemli) | Yazar(lar): Mustafa Ustuner, Fusun Balik Sanli, Gokhan Bilgin, Saygin Abdikan, None None | Yıl: 2017 | Dergi/Kurum: 2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | İndeks: WOS.ISTP | Anahtar Kelimeler: Sentinel 1-A, Synthetic aperture radar, support ve
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.