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首页> 外文期刊>Geophysical Research Letters >Combining remote sensing data and an inundation model to map tidal mudflat regions and improve flood predictions: A proof of concept demonstration in Cook Inlet, Alaska
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Combining remote sensing data and an inundation model to map tidal mudflat regions and improve flood predictions: A proof of concept demonstration in Cook Inlet, Alaska

机译:结合遥感数据和淹没模型来绘制潮汐滩涂区域并改善洪水预报:阿拉斯加库克湾的概念验证

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摘要

Accurate flood predictions require high resolution inundation numerical models and detailed coastal and land topography data. However, such data are not always available. A new method to obtain topographic information of flood zones from remote sensing data is demonstrated here for Cook Inlet, Alaska, where tidal range reaches 8-10 m. The moving shoreline is detected from analysis of water coverage in satellite images taken at different tidal stages, and then the shoreline data from different times are combined with water level data from observations and models to produce new topographic maps of previously unobserved mudflats. The remote sensing-based analysis provides for the first time a way to evaluate the flood predictions of the inundation model of the inlet. The new flood-zone topography obtained from the remote sensing data will help to construct a more accurate inundation model in the future. Citation: Ezer, T., and H. Liu (2009), Combining remote sensing data and a inundation model to map tidal mudflat regions and improve flood predictions: A proof of concept demonstration in Cook Inlet, Alaska, Geophys.
机译:准确的洪水预报需要高分辨率的淹没数值模型以及详细的沿海和陆地地形数据。但是,此类数据并非始终可用。在阿拉斯加的库克湾,这里展示了一种从遥感数据中获取洪水带地形信息的新方法,潮汐范围达到了8-10 m。通过分析在不同潮汐阶段拍摄的卫星图像中的水覆盖率来检测移动的海岸线,然后将来自不同时间的海岸线数据与来自观测值和模型的水位数据相结合,以生成以前未观测到的滩涂的新地形图。基于遥感的分析首次提供了一种方法来评估进口淹没模型的洪水预报。从遥感数据获得的新的洪水区地形将有助于将来构建更准确的淹没模型。引用:Ezer,T.和H. Liu(2009),结合遥感数据和淹没模型来绘制潮汐滩涂区域并改善洪水预报:在阿拉斯加Geophys的Cook Inlet进行概念验证。

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