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Analysis of errors of derived slope and aspect related to DEM data properties

机译:分析与DEM数据属性相关的坡度和坡向的误差

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One of the obvious sources of errors in digital terrain analysis (DTA) algorithms is that introduced by raster data structure employed by a digital elevation model (DEM). Because of its regular sample space and orientation, the DTA results often show significant octant 'bias', presenting obvious visual and numerical error patterns. Moreover, other DEM data properties may also introduce errors in slope and aspect computation, such as data precision and spatial resolution (i.e. grid interval). This paper reports an investigation on the accuracy of algorithms that derive slope and aspect measures from grid DEM. A quantitative methodology has been developed for objective and data-independent assessment of errors generated from the algorithms that extract surface morphological parameters such as slope and aspect from grid DEM.The generic approach is to use artificial surfaces that can be described by a mathematical model, thus the 'true' output value can be pre-determined to avoid uncertainty caused by uncontrollable data errors. Two mathematical surfaces were generated based on ellipsoid (representing convex slopes) and Gauss synthetic surface (representing complex slopes), and the theoretical 'true' value of the slope and aspect at any given point on the surfaces could be computed using mathematical inference. Based on these models, tests were made on the results from a number of algorithms for slope and aspect computation. Analysis has been undertaken to find out the spatial and statistical patterns of error distribution so that the influence of data precision, grid resolution, grid orientation and surface complexity can be quantified. (C) 2004 Elsevier Ltd. All rights reserved.
机译:数字地形分析(DTA)算法中明显的错误源之一是由数字高程模型(DEM)所采用的栅格数据结构引入的。由于其规则的样本空间和方向,DTA结果通常显示出明显的八分圆“偏差”,呈现出明显的视觉和数字错误模式。此外,其他DEM数据属性也可能在坡度和坡向计算中引入错误,例如数据精度和空间分辨率(即网格间隔)。本文报告了对从网格DEM导出坡度和高程度量的算法的准确性的研究。已开发出一种定量方法,用于客观和独立于数据的评估算法产生的误差,这些算法从网格DEM中提取坡度和坡度等表面形态参数,通用方法是使用可通过数学模型描述的人工表面,因此,可以预先确定“真实”输出值,以避免由于不可控制的数据错误而导致的不确定性。基于椭圆体(表示凸坡度)和高斯合成表面(表示复数坡度)生成了两个数学曲面,并且可以使用数学推论来计算曲面上任意给定点的坡度和长宽比的理论“真”值。基于这些模型,对多种坡度和坡向计算算法的结果进行了测试。已进行分析以找出误差分布的空间和统计模式,以便可以量化数据精度,网格分辨率,网格方向和表面复杂性的影响。 (C)2004 Elsevier Ltd.保留所有权利。

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