数据独立的GIS空间内插特性分析
Analysis of Spatial Interpolation Techniques Based On Data-independent Method
摘要
内插是GIS空间分析的基本工具之一。本文从插值机理出发，构造了内插算法的统一模型，提出了数据独立的空间内插评价方法，即首先离散化选取的数学曲面获取无误差采样数据点，然后对其添加随机误差模拟含有不同程度的误差数据，分别进行内插计算，通过内插函数恢复的曲面与原始数学曲面的比较实现对内插方法的评价和抗差性能分析。结果表明：当原始数据质量较好时，薄板样条、克里金等精确性内插方法能给出较为可靠的内插估计，当数据含有较大误差时，局部多项式内插结果优于其他内插算法，同时合理的权函数确定和采样数据误差的有效抑制是提高内插精度的有效途径。
Abstract
Interpolation is one of the most basic GIS analysis methods. Based on the principle of interpolation, this paper firstly constructs a unified interpolation model of different interpolation algorithms, and then proposes an evaluation and analysis approach of spatial interpolation in GIS based on data-independent. 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. And then the artificial surfaces are dispersed to generate the 'true' discrete data which will be employed to reconstruct the surfaces based on different interpolation algorithms. Finally, the actual output values from algorithms on the mathematical surfaces can be compared with the theoretical true values, so the errors are then statistically analyzed, and strengths and weakness of algorithms are evaluated. Based on the proposed approach, several interpolation algorithms were analyzed and evaluated, as well as the robustness to data errors. Some conclusions can be got as follows: when the quality of original data is relatively well, the exact interpolation algorithms such as thin plate spline and Kriging can get a satisfied interpolation result, while the errors of original data are higher, the local polynomial algorithm gives the best interpolation accuracy and shows the strongest robustness to errors, mean while reasonable weight functions and proper error reductions can improve the interpolation accuracy effectively.关键词
地图学与地理信息系统/空间内插/数据独立/抗差性能Key words
Cartography and geography information system/Spatial Interpolation/Data-independent/Robustness引用本文复制引用
胡加佩,刘学军,马锦绢.数据独立的GIS空间内插特性分析[EB/OL].(2011-04-15)[2026-04-02].http://www.paper.edu.cn/releasepaper/content/201104-354.学科分类
地球物理学
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