Flooding is a particular hazard in urban areas worldwide due to the increased risks to life and property in these regions. Synthetic Aperture Radar (SAR) sensors are often used to image flooding because of their all-weather day-night capability, and now possess sufficient resolution to image urban flooding. The flood extents extracted from the images may be used for flood relief management and improved urban flood inundation modelling. ududA difficulty with using SAR for urban flood detection is that, due to its side-looking nature, substantial areas of urban ground surface may not be visible to the SAR due to radar layover and shadow caused by buildings and taller vegetation. This paper investigates whether urban flooding can be detected in layover regions (where flooding may not normally be apparent) using double scattering between the (possibly flooded) ground surface and the walls of adjacent buildings. The method estimates double scattering strengths using a SAR image in conjunction with a high resolution LiDAR (Light Detection and Ranging) height map of the urban area. A SAR simulator is applied to the LiDAR data to generate maps of layover and shadow, and estimate the positions of double scattering curves in the SAR image. ududObservations of double scattering strengths were compared to the predictions from an electromagnetic scattering model, for both the case of a single image containing flooding, and a change detection case in which the flooded image was compared to an un-flooded image of the same area acquired with the same radar parameters. The method proved successful in detecting double scattering due to flooding in the single-image case, for which flooded double scattering curves were detected with 100% classification accuracy (albeit using a small sample set) and un-flooded curves with 91% classification accuracy. The same measures of success were achieved using change detection between flooded and un-flooded images. Depending on the particular flooding situation, the method could lead to improved detection of flooding in urban areas.
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机译：由于这些地区生命和财产风险的增加，洪水在世界范围内是一个特别的危害。合成孔径雷达（SAR）传感器因其全天候的昼夜能力而经常用于成像洪水，并且现在拥有足够的分辨率来成像城市洪水。从图像中提取的洪水范围可以用于洪水管理和改进的城市洪水淹没模型。 。SAR用于城市洪水检测的一个困难是，由于其侧面的性质，由于建筑物和较高植被引起的雷达下垂和阴影，SAR可能看不到市区的大面积区域。本文研究了在（可能是被洪水淹没的）地面与相邻建筑物墙壁之间的双重散射，是否可以在中途停留的区域（通常不会出现洪水泛滥）中检测到城市洪水。该方法使用SAR图像结合市区的高分辨率LiDAR（光检测和测距）高度图来估计双散射强度。将SAR模拟器应用于LiDAR数据以生成叠加图和阴影图，并估计SAR图像中双散射曲线的位置。 ud ud双重散射强度的观测值与电磁散射模型的预测值进行了比较，对于单个包含泛洪的图像，以及将泛洪的图像与未泛洪的图像进行比较的变化检测情况使用相同雷达参数获取的相同区域。该方法在单图像情况下成功地检测了由于泛洪导致的双重散射，该方法检测到泛洪的双散射曲线的分类精度为100％（尽管使用的是小样本集），而未泛滥的曲线的分类精度为91％。使用淹没图像和未淹没图像之间的变化检测，可以实现相同的成功度量。根据特定的洪水情况，该方法可以改善对城市地区洪水的检测。
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