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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 #6 was classified as gully side walls. After distinguishing gullies and cliffs areas among points belonging to cluster 6, all six gullies were satisfactorily identified. The proposed methodology improves on existent techniques because identifies distinct parts of gullies which include side walls and bed zone.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 (θ) had the largest effect on slope stability factor (S.D.1999 = 0.18, S.D.2014 = 0.24), according the sensitivity analysis, compared to variations of soil cohesion, failure plane angle and slab thickness. In addition, critically instable slopes within gully, based on units of the slope standard deviation, as a threshold, have produced an area of 61 m2 and 396 m2 considering the threshold of one and two slope standard deviation, respectively. The majority of these critical areas were located near the headcut and in the border of side walls. Based on current literature, association of processed material (geotextile) and crop cover with high root density might be an alternative to improve slope instability, but empirical tests are necessary to validate this approach. Nevertheless, the slope instability must include other factors that capture the dynamics of failure.
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。簇#6被分类为沟渠侧壁。在区分属于群集6的点之间的沟壑和悬崖区域之后,可以令人满意地识别所有六个沟壑。所提出的方法对现有技术进行了改进,因为它可以识别出沟渠的不同部分,包括侧壁和床层。另一个重要的概念是评估沟渠边坡的稳定性,以便为精确的保护规划提供有用的信息。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方法下爱荷华州西部沟壑区的两次多时相调查,涉及到精确的保护实践。该研究使用源自于1999年和2014年进行的调查显示,与1999年的调查坡度相比,本次评估的结果表明实际坡度的不稳定性大大降低。根据敏感性分析,与土壤内聚力,破坏平面角和板厚的变化相比,内摩擦角(θ)对边坡稳定系数的影响最大(S.D.1999 = 0.18,S.D.2014 = 0.24)。另外,基于坡度标准偏差的单位作为阈值,沟内的严重不稳定坡度分别考虑到一个和两个坡度标准偏差的阈值产生了61 m2和396 m2的面积。这些关键区域中的大多数位于靠近割口和侧壁的边界。根据目前的文献,加工材料(土工布)和高根部密度的作物覆盖物之间的关联可能是改善边坡不稳定性的一种替代方法,但是必须进行经验测试以验证这种方法。尽管如此,边坡的不稳定性必须包括捕获破坏动态的其他因素。

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