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Near Real-Time Flood Detection in Urban and Rural Areas Using High-Resolution Synthetic Aperture Radar Images

机译:使用高分辨率合成孔径雷达图像的城乡近实时洪水探测

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A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high-resolution synthetic aperture radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high-resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18%, respectively.
机译:概述了城市和农村地区洪水泛滥的概貌的近实时洪水检测算法,即使存在云,它也能够在夜间和白天工作,这可能是操作洪水的有用工具救济管理。本文介绍了一种基于高分辨率合成孔径雷达(SAR)卫星数据的自动算法,该算法基于现有方法,包括在对象分类之前使用图像分割技术来应对这些场景中的大量像素。城市地区的洪水检测以邻近农村地区的洪水范围为指导。该算法假定高分辨率地形高度数据至少可用于场景的市区,以便可以使用SAR模拟器来估计雷达阴影和中转的区域。该算法被证明能够使用TerraSAR-X准确检测农村地区的洪水,正确分类了89%的洪水像素,相关的假阳性率为6%。 TerraSAR-X可视的城市水像素中,正确检测到75%,假阳性率为24%。如果考虑所有城市水像素,包括阴影地区和中转地区的像素,这些数字分别降至57%和18%。

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