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A combined algorithm for automated drainage network extraction from digital elevation models

机译:从数字高程模型中自动提取排水网络的组合算法

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摘要

Drainage networks are the basis for segmentation of watersheds, an essential component in hydrological modelling, biogeochemical applications, and resource management plans. With the rapidly increasing availability of topographic information as digital elevation models (DEMs), there have been many studies on DEM-based drainage network extraction algorithms. Most of traditional drainage network extraction methods require preprocessing of the DEM in order to remove "spurious" sink, which can cause unrealistic results due to removal of real sinks as well. The least cost path (LCP) algorithm can deal with flow routing over sinks without altering data. However, the existing LCP implementations can only simulate either single flow direction or multiple flow direction over terrain surfaces. Nevertheless, terrain surfaces in the real world are usually very complicated including both convergent and divergent flow patterns. The triangular form-based multiple flow (TFM) algorithm, one of the traditional drainage network extraction methods, can estimate both single flow and multiple flow patterns. Thus, in this paper, it is proposed to combine the advantages of the LCP algorithm and the TFM algorithm in order to improve the accuracy of drainage network extraction from the DEM. The proposed algorithm is evaluated by implementing a data-independent assessment method based on four mathematical surfaces and validated against "true" stream networks from aerial photograph, respectively. The results show that when compared with other commonly used algorithms, the new algorithm provides better flow estimation and is able to estimate both convergent and divergent flow patterns well regarding the mathematical surfaces and the real-world DEM.
机译:排水网络是流域分割的基础,是水文建模,生物地球化学应用和资源管理计划中的重要组成部分。随着地形信息作为数字高程模型(DEM)的迅速增加,已经进行了许多基于DEM的排水网络提取算法的研究。大多数传统的排水管网抽取方法都需要对DEM进行预处理,以去除“虚假”的水槽,由于去除了真实的水槽,这也可能导致不切实际的结果。成本最低的路径(LCP)算法可以处理接收器上的流路由,而无需更改数据。但是,现有的LCP实现只能在地形表面上模拟单个流向或多个流向。然而,现实世界中的地形表面通常非常复杂,包括会聚和发散的流型。基于三角形形式的多流(TFM)算法是传统的排水网络提取方法之一,可以估计单流和多流模式。因此,本文提出了结合LCP算法和TFM算法的优点,以提高从DEM中提取排水网络的准确性。通过实施基于四个数学面的数据独立评估方法对所提出的算法进行评估,并分别针对航空照片中的“真实”流网络进行了验证。结果表明,与其他常用算法相比,该新算法提供了更好的流量估计,并且能够在数学曲面和实际DEM方面很好地估计收敛和发散的流量模式。

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