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Remote sensing of river stage using the cross‐sectional inundation area‐river stage relationship (IARSR) constructed from digital elevation model data

机译:利用数字高程模型数据构建的横断面淹没面积与河川水位关系(IARSR)遥感河段

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Remote sensing of discharge and river stage from space provides us with a promising alternative approach to monitor watersheds, no matter if they are ungauged, poorly gauged, or fully gauged. One approach is to estimate river stage from satellite measured inundation area based on the inundation area – river stage relationship (IARSR). However, this approach is not easy to implement because of a lack of data for constructing the IARSR. In this study, an innovative and robust approach to construct the IARSR from digital elevation model (DEM) data was developed and tested. It was shown that the constructed IARSR from DEM data could be used to retrieve water level or river stage from satellite-measured inundation area. To reduce the uncertainty in the estimated inundation area, a dual-thresholding method was proposed. The first threshold is the lower limit of pixel value for classifying water body pixels with a relatively high-level certainty. The second threshold is the upper limit of pixel value for classifying potentially flooded pixels. All pixels with values between the first threshold and the second threshold and adjacent to the classified water body pixels may be partially flooded. A linear interpolation method was used to estimate the wetted area of each partially flooded pixel. In applying the constructed IARSR to the estimated inundation areas from 11 Landsat TM images, 11 water levels were obtained. The root mean square error (RMSE) of the estimated water levels compared with the observed water levels at the US Geological Survey (USGS) gauging station on the Trinity River at Liberty in Liberty County, Texas, is about 0.38 m. Copyright © 2012 John Wiley & Sons, Ltd.
机译:不论空间是未注水,量度不佳还是完全量度,从太空对排水和河段的遥感都为我们提供了一种有前途的监测流域的替代方法。一种方法是根据淹没面积与河流水位的关系(IARSR)从卫星测得的淹没面积估算河流水位。但是,由于缺少用于构造IARSR的数据,因此该方法不容易实现。在这项研究中,开发和测试了一种创新且强大的方法,可以从数字高程模型(DEM)数据构造IARSR。结果表明,由DEM数据构建的IARSR可用于从卫星测得的淹没区域检索水位或河段。为了减少估计淹没面积的不确定性,提出了一种双阈值方法。第一阈值是用于以相对较高的确定性对水体像素进行分类的像素值的下限。第二阈值是用于分类潜在淹没像素的像素值的上限。值在第一阈值和第二阈值之间并且与分类的水体像素相邻的所有像素可以被部分淹没。使用线性插值方法来估计每个部分淹没像素的润湿区域。将构建的IARSR应用到11个Landsat TM图像估算的淹没区域中,获得了11个水位。估计水位的均方根误差(RMSE)与在得克萨斯州自由县利伯蒂的三一河上的美国地质调查局(USGS)计量站观察到的水位相比,约为0.38μm。版权所有©2012 John Wiley&Sons,Ltd.

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