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首页> 外文期刊>Geomorphology >An automated method to extract fluvial terraces from digital elevation models: The Vesdre valley, a case study in eastern Belgium
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An automated method to extract fluvial terraces from digital elevation models: The Vesdre valley, a case study in eastern Belgium

机译:从数字高程模型中提取河流阶地的自动化方法:维斯德河谷,比利时东部的案例研究

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Fluvial terraces are a powerful tool for unraveling the combined tectonic and climatic conditions that controlled, directly or indirectly, the Quaternary incision of rivers. Terrace long profiles are usually retrieved from sparse traces of ancient floodplains preserved in the present topography. However, when these traces classically collected from topographic maps, aerial photographs, and field analyses are too few, the inferred profiles may be questionable. Yet the now available high quality and high resolution digital elevation models (DEMs) offer an opportunity to increase greatly the quantity of information usable to reconstruct terrace profiles. Therefore, the purpose of this study was to develop a new DEM-based method of terrace recognition in order to create a larger database and better constrain the profile reconstruction. Moreover, particular procedures of image and numerical processing were defined to fully automate the analysis. Basically, our method relies on the production of bivariate scatter plots depicting the relation between slope and relative altitude (i.e., the altitude above the current alluvial plain) for all pixels of successive sections of the valley. For each scatter plot, the curve of the lowest slope values observed at every relative altitude is smoothed and its minima are assumed to locate the altitudes of the "terrace" elements preserved in the section. We successfully tested this method in the Vesdre valley, incised in the NE Ardenne massif (E Belgium), notably identifying fault deformation of the profiles. The main advantages of our approach are its objectivity, exhaustiveness, and rapidity, allowing fast and coherent analysis of many rivers over extended regions.
机译:河流阶地是揭露直接或间接控制河流第四纪切口的构造和气候条件组合的有力工具。梯田长剖面通常是从保存在当前地形中的古代洪泛区的稀疏痕迹中获取的。但是,当从地形图,航拍照片和现场分析中经典收集的这些痕迹太少时,推断出的剖面可能会令人怀疑。然而,现在可用的高质量和高分辨率数字高程模型(DEM)提供了一个机会,可以大大增加可用于重建阶地剖面的信息量。因此,本研究的目的是开发一种新的基于DEM的梯田识别方法,以创建一个更大的数据库并更好地约束轮廓重建。此外,定义了图像和数值处理的特定程序以完全自动化分析。基本上,我们的方法依赖于二元散点图的产生,该散点图描述了谷底连续部分的所有像素的坡度与相对高度(即当前冲积平原以上的高度)之间的关系。对于每个散点图,在每个相对高度观察到的最低斜率值的曲线都经过平滑处理,并假定其最小值位于该部分中保留的“露台”元素的高度上。我们在NE Ardenne地块(比利时E)的Vesdre山谷成功地测试了该方法,特别是识别了剖面的断层变形。我们的方法的主要优点是它的客观性,详尽性和快速性,可以对扩展区域内的许多河流进行快速而连贯的分析。

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