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Natural Neighbors Interpolation Method for Correcting IDW

机译:修正IDW的自然邻域内插方法

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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:数字高程模型(DEM)插值是GIS和相关空间信息领域中用于空间描述和空间分析的基本功能之一。可以将插值视为使用一组适当的已知数据来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中最常用的方法。 IDW选择的参考点可能无法在空间中很好地分布。这会导致插值DEM表面的不连续性问题,并且可能会生成一些伪像。为了解决搜索过程中参考点数目和位置分布不均的问题,提出了一种关于一阶自然邻域插值的曲面插值模型。基于TIN的一阶自然邻居插值的使用可以很好地适应不良的数据分布,因为插入点会生成定义良好的邻居集。在拟合过程中,根据一阶自然邻点和以三角形区域为已知点的权重基础的影响范围,可以构造一个非线性拟合方程。对比实验表明,该方法具有较高的精度和更实用的应用价值。

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