Volume XLI-B7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 371-378, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-371-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 371-378, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-371-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  21 Jun 2016

21 Jun 2016

A FUZZY LOGIC-BASED APPROACH FOR THE DETECTION OF FLOODED VEGETATION BY MEANS OF SYNTHETIC APERTURE RADAR DATA

V. Tsyganskaya1,2, S. Martinis2, A. Twele2, W. Cao2, A. Schmitt2, P. Marzahn1, and R. Ludwig1 V. Tsyganskaya et al.
  • 1Ludwig-Maximilians-Universität München, Department of Geography, Luisenstr. 37, 80333 Munich, Germany
  • 2German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Oberpfaffenhofen, 82234 Wessling, Germany

Keywords: Fuzzy logic, Flooded vegetation, Synthetic Aperture Radar (SAR), Data fusion, TerraSAR-X

Abstract. In this paper an algorithm designed to map flooded vegetation from synthetic aperture radar (SAR) imagery is introduced. The approach is based on fuzzy logic which enables to deal with the ambiguity of SAR data and to integrate multiple ancillary data containing topographical information, simple hydraulic considerations and land cover information. This allows the exclusion of image elements with a backscatter value similar to flooded vegetation, to significantly reduce misclassification errors. The flooded vegetation mapping procedure is tested on a flood event that occurred in Germany over parts of the Saale catchment on January 2011 using a time series of high resolution TerraSAR-X data covering the time interval from 2009 to 2015. The results show that the analysis of multi-temporal X-band data combined with ancillary data using a fuzzy logic-based approach permits the detection of flooded vegetation areas.