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Classical gully spatial identification and slope stability modeling using high-resolution elevation and data mining technique.

机译:使用高分辨率高程和数据挖掘技术的经典沟壑空间识别和边坡稳定性建模。

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摘要

It is widely known that soil erosion is an issue of concern in soil and water quality, affecting agriculture and natural resources. Thus, scientific efforts must take into consideration the high-resolution elevation dataset in order to implement a precision conservation approach effectively. New advances such as LiDAR products have provided a basic source of information to enable researchers to identify small erosional landscape features. To fill this gap, this study developed a methodology based on data mining of hydrologic and topographic attributes associated with concentrated flow path identification to distinguish classic gully side walls and bed areas. At 0.91 Km2 region of the Keigley Branch-South Skunk River watershed, an area with gullies, we computed profile curvature, mean slope deviation, stream power index, and aspect gridded in 1-m pixel from Iowa LiDAR project. CLARA (CLustering LARge Applications) algorithm. An unsupervised clustering approach was employed on 913,495 points splitting the dataset in six groups, the number in agreement with within-group sum of squared error (WSS) statistical technique. In addition, a new threshold criteria termed gully concentrated flow (GCF) based upon data distribution of flow accumulation and mean overall slope were introduced to produce polylines that identified the main hydrographic flow paths, corresponding to the gully beds. Cluster ;Another important concept is assessing gully slope stability in order to generate useful information for precision conservation planning. Although limit-equilibrium concept has been used widely in rock mechanics its application in precision conservation structures is relatively new. This study evaluated two multi-temporal surveys in a Western Iowa gullied area under the approach of soil stability regarding precision conservation practice The study computed factor of safety (FS) at the gully area, including headcut and gully side walls using digital elevation models originated from surveys conducted in 1999 and 2014.;Outcomes of this assessment have revealed significantly less instability of the actual slopes compared to 1999 survey slopes. The internal friction angle (&
机译:众所周知,水土流失是土壤和水质问题,影响农业和自然资源。因此,科学努力必须考虑高分辨率高程数据集,以便有效地实施精确的保护方法。诸如LiDAR产品之类的新进展提供了基本的信息来源,使研究人员能够识别出较小的侵蚀性景观特征。为了填补这一空白,本研究开发了一种基于数据挖掘的水文和地形属性的方法,该属性与集中流路识别相关联,以区分经典的沟壑侧壁和河床区域。在爱荷华州LiDAR项目的1-m像素的Keigley分支-南臭鼬河分水岭(一个有沟壑的区域)的0.91 Km2区域,计算了剖面曲率,平均坡度偏差,流功率指数和纵横比。 CLARA(大型应用程序)算法。对913,495个点采用了无监督聚类方法,将数据集分为六个组,该数量与组内平方误差和(WSS)统计技术相符。此外,引入了一种新的阈值标准,该标准基于流量累积的数据分布和平均总坡度,称为沟汇集中流量(GCF),以生成识别对应于沟床的主要水文流道的折线。集群;另一个重要的概念是评估沟渠边坡的稳定性,以便为精确的养护规划生成有用的信息。尽管极限平衡概念已在岩石力学中得到广泛应用,但其在精密养护结构中的应用相对较新。这项研究评估了在土壤稳固性保护方法下爱荷华州西部沟壑区的两次多时相调查,该研究使用精确的数字高程模型计算了沟壑区的安全系数(FS),包括顶切和沟渠侧壁。在1999年和2014年进行的调查;该评估的结果表明,与1999年的调查坡度相比,实际坡度的不稳定性大大降低。内摩擦角(&

著录项

  • 作者单位

    Iowa State University.;

  • 授予单位 Iowa State University.;
  • 学科 Agricultural engineering.;Computer science.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 121 p.
  • 总页数 121
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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