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Flooding Water Depth Estimation With High-Resolution SAR

机译:高分辨率SAR的洪水水深估算

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摘要

The retrieval of flooding levels with high-resolution (HR) synthetic aperture radar (SAR) images is presented in this paper. A new framework is proposed. It is based on the inversion of theoretical scattering models initially developed for nonflooded urban areas and here adapted to the flooding case. Starting from the theory, two possible retrieval approaches have been developed and are the main topic of this paper: two possible retrieval approaches have been developed and are the main topic of this paper: the local Single Image Objects Aware (SIObA) and the global Two Image Area Aware (TIArA). These two approaches are conceived to be applicable under different working conditions and consequently holding different properties and reliability. For each of them, a different algorithm is derived and tested, and the retrieval results are validated on a meaningful data set of HR TerraSAR-X images relevant to the Gloucestershire (U.K.) flooding that occurred in year 2007.
机译:本文提出了高分辨率(HR)合成孔径雷达(SAR)图像的洪水位的检索。提出了一个新的框架。它基于最初为非淹没城市地区开发的理论散射模型的反演,此处适用于洪水情况。从理论出发,已经开发了两种可能的检索方法,它们是本文的主要主题:已经开发了两种可能的检索方法,并且是本文的主要主题:本地单图像对象感知(SIObA)和全局两种。图像区域感知(TIArA)。这两种方法被认为适用于不同的工作条件,因此具有不同的性能和可靠性。对于它们中的每一个,都导出并测试了不同的算法,并且对与2007年发生的格洛斯特郡(英国)洪水有关的HR TerraSAR-X图像的有意义的数据集验证了检索结果。

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