Exploring scaling laws in surface topography
Exploring scaling laws in surface topography
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DOI：
10.1016/j.chaos.2009.03.121
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发表时间：
2009-11-30
影响因子：
7.8
通讯作者：
Shaghaghian, M. R.
中科院分区：
文献类型：
--
作者：
Abedini, M. J.;Shaghaghian, M. R.
地表地形影响许多土壤性质和过程，特别是地表水储存和径流。分形分析的应用有助于理解在广泛的空间尺度和气候制度的表面地形固有的标度律。在这项研究中，一个高分辨率的数字高程模型与3撕裂分辨率的光谱和大规模DEM的一边，与500米的空间分辨率的另一边被用来探索表面地形的比例尺律。通过对这两种类型的数据集进行适当的探索性空间数据分析，两种传统的计算程序-变差函数和盒计数法（BOX）-解决了表面地形的标度律。结果尊重表面形貌的标度律在一定程度上，无论是情节处理，也没有方向处理分形维数变异有显着的影响。而在变差函数方法中，Richardson图中斜率的变化似乎是正常的，而不是例外; Richardson的图由盒计数实现产生，缺乏这样的数学行为。这些斜坡上的突变可能对划分同质水文单元和检测水文时间序列中的趋势变化具有有用的意义。此外，它表明，分形维数不能用来捕捉各向异性的变异内和之间的微观图。此外，它的数值保持在5%的水平，从一个方向移动到另一个，也从一个空间尺度到另一个不显著，而纵坐标截距可以区分表面粗糙度变异从一个空间尺度到另一个。(c)2009爱思唯尔有限公司保留所有权利。
Surface topography affects many soil properties and processes, particularly surface water storage and runoff. Application of fractal analysis helps understand the scaling laws inherent in surface topography at a wide range of spatial scales and climatic regimes. In this research, a high resolution digital elevation model with a 3 torn resolution on one side of the spectrum and large scale DEMs, with a 500 m spatial resolution on the other side were used to explore scaling laws in surface topography. With appropriate exploratory spatial data analysis of both types of data sets, two conventional computational procedures - variogram and Box Counting Methods (BCM) - address scaling laws in surface topography. The results respect scaling laws in surface topography to some extent as neither the plot treatment nor the direction treatment has a significant impact on fractal dimension variability. While in the variogram method, the change in slope in Richardson's plots appears to be the norm rather than the exception; Richardson's plots resulting from box counting implementation lack such mathematical behavior. These breaks in slope might have useful implications for delineating homogeneous hydrologic units and detecting change in trend in hydrologic time series. Furthermore, it is shown that fractal dimension cannot be used to capture anisotropic variabilities both within and among micro-plots. In addition, its numerical value remains insignificant at the 5% level in moving from one direction to another and also from one spatial scale to another while the ordinate intercept could discriminate the surface roughness variability from one spatial scale to another. (c) 2009 Elsevier Ltd. All rights reserved.