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Natural Neighbors Interpolation Method for Correcting IDW

机译:纠正IDW的自然邻居插值方法

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Digital Elevation Model (DEM) interpolation is one of basic functions for spatial description and spatial analysis in GIS and related spatial information fields. Interpolation can be viewed as a function for estimating the heights of unknown points using a set of proper known data. It is a key problem of DEM. Inverse distance weighting (IDW) interpolation is the most commonly used in DEM. The reference points selected by IDW might not be well distributed in space. This leads to the discontinuity problem of interpolated DEM surface and some artifacts might be generated. In order to solve the problem caused by ill-distribution of the number and position of reference points in searching process, this paper put forward a new surface interpolation model about first-order natural neighbor interpolation. The use of first-order natural neighbor interpolation based on TIN can adapt well to poor data distributions because inserting into a point generates a well-defined set of neighbors. In the fitting process, according to range of influence composed by first-order natural neighbor points and the triangle area as weight base of the known point, a non-linear fitting equation can be constructed. Comparative experiments show that this method has higher precision and more practical application value.
机译:数字高度模型(DEM)插值是GIS和相关空间信息字段中空间描述和空间分析的基本功能之一。可以将插值视为用于使用一组正确已知数据估计未知点的高度的函数。这是DEM的关键问题。逆距离加权(IDW)插值是DEM中最常用的。 IDW选择的参考点可能在空间中不得很好地分布。这导致内插DEM表面的不连续性问题,并且可能产生一些伪影。为了解决搜索过程中参考点数量和位置的命运和位置造成的问题,本文提出了关于一阶天然邻插值的新表面插值模型。使用基于锡的一阶天然邻插值可以适应差的数据分布,因为插入点生成一组明确定义的邻居集。在拟合过程中,根据由一阶天然邻点和三角形区域组成的影响范围作为已知点的权重基础,可以构造非线性拟合方程。比较实验表明,该方法具有更高的精度和更实际的应用价值。

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