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A fuzzy logic-based approach for the detection of flooded vegetation by means of Synthetic Aperture Radar data

机译:基于模糊逻辑的合成孔径雷达数据检测水淹植被

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摘要

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.
机译:本文介绍了一种用于从合成孔径雷达(SAR)图像中绘制淹没植被的地图的算法。该方法基于模糊逻辑,该模糊逻辑能够处理SAR数据的歧义性,并整合包含地形信息,简单水力考虑因素和土地覆盖信息的多个辅助数据。这允许排除具有类似于淹没植被的反向散射值的图像元素,从而显着减少分类错误。使用涵盖2009年至2015年时间间隔的高分辨率TerraSAR-X数据的时间序列,对2011年1月德国萨勒河集水区部分地区发生的洪水事件进行了水淹植被测绘程序的测试。结果表明,该分析使用基于模糊逻辑的方法对多时相X波段数据与辅助数据进行组合,可以检测淹没的植被区域。

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