In the thin-plate smoothing splines interpolation, the accuracy of interpolation results is mainly determined by choosing the independent covariate. Annual precipitation data were extracted by using daily precipitation data of 728 meteorological stations from 2001 to 2009 in China. We evaluated spatial correlation relationships between annual precipitation and two covariates such as DEM and distance from the coastline to each point (DCL) and compared the accuracy difference of precipitation interpolation results from different covariates in the national scale and regional scale. All interpolation work has been conducted with the aid of the software of ANUSPLIN. We used three interpolation methods, which respectively considered DEM, DCL and DEM-DCL as the covariates to obtain spatial distribution of precipitation. Our analyses show that, (1) in the national scale, the mean absolute error (MAE) of interpolation method of DEM is 47.79, which is slightly lower than that of the method of DEM-DCL (48.90), while obviously lower than that of the method of DCL (55.54), and MRE and RMSE of the method of DEM were also lower than other two methods significantly. (2) In regional scale, the errors of three methods of interpolation are the same as that in national scale except Tibet. The accuracy of precipitation interpolation results was the highest using DCL method, and the poorest using DEM method. Results suggest that precipitation interpolation method of DEM could be widely used in some relevant national scale researches, and precipitation interpolation method of DCL was strongly recommended in Tibet.
LIU Zhengjia, YU Xingxiu, WANG Sisi, SHANG Guiduo
. Comparative Analysis of Three Covariates Methods in Thin-Plate Smoothing Splines for Interpolating Precipitation[J]. PROGRESS IN GEOGRAPHY, 2012
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DOI: 10.11820/dlkxjz.2012.01.008
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