Flooding Water Depth Estimation With High-Resolution SAR
Flooding Water Depth Estimation With High-Resolution SAR
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DOI：
10.1109/tgrs.2014.2358501
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发表时间：
2015-05
影响因子：
8.2
通讯作者：
Pasquale Iervolino;R. Guida;A. Iodice;D. Riccio
中科院分区：
文献类型：
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作者：
Pasquale Iervolino;R. Guida;A. Iodice;D. Riccio
提出了一种利用高分辨率合成孔径雷达（SAR）图像反演洪水位的方法。提出了一个新的框架。它是基于反演的理论散射模型最初开发的非淹没城市地区，在这里适应洪水的情况下。从理论出发，两种可能的检索方法已经开发，是本文的主要议题：两种可能的检索方法已经开发，是本文的主要议题：本地单图像对象感知（SIOBA）和全球两个图像区域感知（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。对于他们中的每一个人，一个不同的算法推导和测试，检索结果进行了验证的一个有意义的数据集的HR TerraSAR-X图像相关的格洛斯特郡（英国）。2007年发生的洪水。
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.