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Smoothing of digital elevation models and the alteration of overland flow path length distributions

机译:平滑数字高度模型及陆地流动路径长度分布的改变

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DEM smoothing is a common pre-processing technique used to remove undesirable roughness from a DEM. However, it is hypothesized that smoothing straightens and reduces the length of overland flow paths, which is an important factor controlling modelled time-to-peak flow. Currently, there is a lack of research comparing how different smoothing techniques alter the distribution of overland flow path length. Four low-pass filtering techniques were applied to three fine-resolution LiDAR DEMs of varying relief: the mean filter, the median filter, the Gaussian filter, and the feature-preserving DEM smoothing (FPDEMS) filter, each with different degrees of smoothing. Downslope-distance-to-stream distributions were then derived using D8 and D infinity flow directions and statistically compared to distributions derived from the unsmoothed DEM for each study site. The results indicate that the alteration of flow path length distributions as a result of smoothing is complex. Mean flow path lengths may decrease or increase in response to smoothing, depending on landscape relief and the derivation of flow directions, and generalized flow paths may become longer. The largest increase in mean flow path lengths was 19.2 m using the 21 x 21 median filter and D8 flow directions in the high-relief study site, relative to an unsmoothed mean length of 138.6 m in this site. The largest decrease in mean flow path length was 48.9 m using the 21 x 21 mean filter and D infinity flow directions in the low-relief study site, relative to an unsmoothed mean length of 290.9 m in this site. Furthermore, minimal flow path length alterations were achieved with the Gaussian filter when gentle smoothing is required, and with the FPDEMS filter when moderate to aggressive smoothing is required. These results suggest that an appropriate smoothing method should be chosen based on the relief of the landscape and the degree of smoothing required.
机译:DEM平滑是一种常见的预处理技术,用于从DEM中移除不期望的粗糙度。然而,假设平滑直升并降低陆孔流动路径的长度,这是控制建模时间到峰流量的重要因素。目前,缺乏研究比较不同的平滑技术如何改变陆陆流动路径长度的分布。将四种低通滤波技术应用于不同浮雕的三个精细分辨率的LIDAR DEM:平均过滤器,中值滤波器,高斯滤波器和特征保留的DEM平滑(FPDEMS)过滤器,每个滤波器具有不同程度的平滑。然后使用D8和D Infinity流程来源地导出距离流距离到流分布,并与来自每个研究现场的无缝DEM导出的分布进行统计学。结果表明,由于平滑的结果,流路长度分布的改变是复杂的。根据横向浮雕和流动方向的推导,平均流动路径长度可以减小或增加响应平滑,并且广义流动路径可能变长。平均流动路径长度的最大增加是19.2米,使用21 x 21中值滤波器和D8流动方向在该网站中的令人毛骨悚然的平均长度为138.6米。使用21 x 21平均过滤器和低浮雕研究部位的平均过滤器和D无限流动方向的最大值减小为48.9μm,在该网站中相对于令人暗中平滑的平均平均长度为290.9米。此外,当需要温和平滑时,通过高斯滤波器实现最小的流路长度改变,并且在需要中等以进行激进平滑时,使用FPDEMS滤波器。这些结果表明,应基于景观的浮雕和所需的平滑度的浮雕来选择适当的平滑方法。

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