Geostatistical space-time modeling for temperature estimation
Geostatistical space-time modeling for temperature estimation
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DOI：
10.1109/agro-geoinformatics.2012.6311707
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发表时间：
2012-09
期刊：
影响因子：
--
通讯作者：
Linwei Sha
中科院分区：
文献类型：
--
作者：
Linwei Sha
气温是一种具有时空特征的重要环境现象。为了实现时空场任意点的时空插值，对东北三省（黑龙江、吉林和辽宁）1972年1月至2008年12月的月平均气温选取了一种实用的积和协方差进行时空建模。由于每个站点的温度可以看作是一个时间序列，因此对其进行分解，去除季节部分，生成残差，以便在时空上进行进一步分析。在纯空间和纯时间变异函数的基础上建立了时空变异函数。将二维克里格法扩展到三维克里格法，估算了2008年1月各站的月平均气温，并与空间克里格法进行了比较。对比结果表明，时空插值是可行的，由于考虑了空间和时间的相关性，其精度优于空间克里格插值。
Air temperature is one of important environmental phenomena with both spatial and temporal characteristics. In order to realize spatial-temporal interpolation at any point in space-time field, a kind of practical product-sum covariance for spatial-temporal modeling is chosen for monthly average air temperature in the three provinces (Heilongjiang, Jilin and Liaoning Province) of Northeast China from January 1972 to December 2008. As every station's temperature can be regarded as a time series, decomposition is processed and seasonal part is removed, and the residuals are generated for further analysis in space-time. Spatial-temporal variogram is built based on the ones of pure space and pure time. Extending 2d-kriging to 3d, the monthly average temperatures of all stations in January 2008 are estimated, and the effect is compared with spatial kriging. The result of compare shows that spatial-temporal interpolation is practical, and because of considering the correlation of both space and time, its accuracy is better than that of spatial kriging.