基于武汉市空气质量指数的不同克里格插值方法性能分析

Yan Tong, Yanc Yu, Xingbang Hu, Li He
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引用次数: 4

摘要

为探讨普通克里格插值方法不同模型对插值结果的影响,验证其在实践中的可行性,本文以武汉市10个空气质量监测点的月平均空气质量指数数据为基础,分别采用球面模型、指数模型和高斯模型进行了插值实验研究。采用实际渲染效果和交叉验证法对插值结果进行定性分析和定量评价。实验结果表明:(1)对于同一数据,不同模型的视觉渲染效果总体上基本一致,但插值精度不同;(2)球面模型的平均标准化误差和均方根误差最大;(3)指数模型的平均误差最小,均方根误差最接近平均标准误差,均方根标准误差最接近1;(4)高斯模型的均值误差最大,但均值标准化误差和均方根误差都最小,均方根误差离平均标准误差最远,均方根标准化误差离1最远。
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Performance analysis of different kriging interpolation methods based on air quality index in Wuhan
To explore the influence on interpolation results in different models of ordinary kriging interpolation methods and to validate their feasibility in practice, the interpolation experimental study using Spherical, Exponential and Gaussian models were carried out in this paper, based on the monthly average Air Quality Index data of 10 air quality sites in Wuhan, China. The interpolation results were qualitatively analyzed and quantitatively evaluated by the actual render effect and cross-validation method. The experimental results demonstrate that: (1) for the same data, the visual render effect in different models are almost the same in the whole, but the interpolation accuracies are different; (2) the Mean Standardized error and Root-Mean-Square error of the Spherical model are the largest; (3) the Mean error of the Exponential model is minimal, the Root-Mean-Square error is nearest to Average Standard Error, and its Root-Mean-Square Standardized error is closest to 1; (4) the Mean error of the Gaussian model is the largest, but both Mean Standardized error and Root-Mean-Square error are minimal, the Root-Mean-Square error is farthest away from Average Standard error, and also its Root-Mean-Square Standardized error is farthest away from the value 1.
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