The paper discusses the opportunities of remote sensing data application as one of the main sources of information for monitoring river floods. Effective operation of flood forecasting systems requires reliable real-time data on inundation areas for timely calibration and verification of the used hydrodynamic models. The opportunity to obtain data from optical sensors might be limited because of dense cloud cover. Synthetic aperture radar (SAR) techniques are increasingly used today due to ability to operate independently of the surface illumination and the state of cloud cover receiving high spatial resolution data in near real-time mode. An important feature of SAR from space today is the increase in the number of freely distributed space data, in particular — images from Sentinel satellites developed by the European Space Agency. For instance, for the territory of Russia Sentinel-1 performs SAR imaging with 2–3 days coverage frequency. Within the framework of the project carried out by the authors, the research area is the city of Velikiy Ustuyg (Russia) located at the confluence of rivers Suhona and Ug. To identify flooded areas the RADARSAT-2 and Sentinel-1 images classification based on thresholding was carried out in open-source software. The visualization of the results was performed on the basis of information analytical system “Prostor”. The results of SAR data processing were compared with contours obtained on the basis of the calculation of the NDWI index from optical data from the Sentinel-2 and Resurs-P satellites. According to the spatial resolution of the data and the selected processing technology, it is possible to achieve high accuracy of flood mapping in open areas with low urbanization. The result confirms that SAR data can be successfully applied for operational flood forecasting.