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A statistical simulation model for positional error of line features in geographic information systems (GIS)

机译:地理信息系统(GIS)中线要素位置误差的统计仿真模型

摘要

This paper presents a new error band model, the statistical simulation error model, for describing the positional error of line features by incorporating both analytical and simulation methods. In this study, line features include line segments, polylines, and polygons. In existing error models, an infinite number of points on the line segment are considered as the stochastic variables and the error band of a line segment is obtained from the union of all intermediate points on the line segment, while that of a polyline/polygon is obtained from the union of all error bands of the composite line segments. Our proposed error band model, however, regards the entire line feature (line segment/polyline/polygon) as the stochastic variable, instead of the infinite number of points on the line segment. Based solely on the statistical characteristics of the endpoints of the line feature and the predefined confidence level, our proposed error model is created by a simulation method that integrates a population of line segments/polylines/polygons computed from the entire solution set of the error model's defining equation. A comprehensive comparison of the proposed and existing error band models is carried out through both simulated and practical experiments. The experimental results show the following: (1) For line segments, the proposed standard statistically simulated error band matches that of existing error models (for example, the G-band). Further, it is found that a scaled G-band with a specific scale factor (e.g., √X2 4(σ)) matches the proposed statistically simulated error band with probability (1-α)×100%. (2) For polylines and polygons, if we correlate the errors of all the endpoints of the polyline/polygon, there is a marked difference between the proposed statistically simulated error band and existing error bands. The reason for the difference is explained as follows. The existing error model defines the error band of a polyline/ polygon as the union of all error bands of the composite line segments, thereby only accounting for the correlation between the two endpoints of each composite line segment. However, our proposed error band model considers the entire polyline/polygon as a whole by accounting for the variance-covariance matrix of all vertices of the polyline/polygon when constructing the statistically simulated error band.
机译:本文提出了一种新的误差带模型,即统计模拟误差模型,该模型通过结合分析和模拟方法来描述线要素的位置误差。在这项研究中,线要素包括线段,折线和多边形。在现有的误差模型中,线段上的无数点被视为随机变量,线段的误差带是从线段上所有中间点的并集获得的,而折线/多边形的误差带是从组合线段的所有误差带的并获得。但是,我们提出的误差带模型将整个线要素(线段/折线/多边形)视为随机变量,而不是线段上的无穷多个点。仅基于线要素端点的统计特性和预定义的置信度,我们提出的误差模型是通过模拟方法创建的,该方法将根据误差模型的整个解集计算出的线段/折线/多边形的总体进行积分定义方程式。通过模拟和实际实验对提议的和现有的误差带模型进行了全面的比较。实验结果表明:(1)对于线段,建议的标准统计模拟误差带与现有误差模型的误差带匹配(例如,G带)。此外,发现具有特定比例因子(例如,√X2 4(σ))的比例缩放的G带以概率(1-α)×100%匹配所提出的统计模拟误差带。 (2)对于折线和多边形,如果我们将折线/多边形的所有端点的误差相关联,则建议的统计模拟误差带与现有误差带之间存在明显差异。差异的原因解释如下。现有的误差模型将折线/多边形的误差带定义为复合线段的所有误差带的并集,从而仅考虑了每个复合线段的两个端点之间的相关性。但是,我们提出的误差带模型在构建统计模拟误差带时,通过考虑折线/多边形的所有顶点的方差-协方差矩阵来考虑整个折线/多边形。

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