Comparative Analysis of Single and Mixed Spatial Interpolation Methods for Variability Prediction of Temperature Prediction
نویسندگان
چکیده
This paper analyzes the validity of temperature maps obtained by means of single and mixed interpolation methods. In this context, several interpolation methods are used for the temperature mapping: inverse distance square (IDS), ordinary kriging (OK) and co-kriging (CK) and mixed methods (combined global, local and geostatistical methods). And the validity of the maps is checked through the cross-validation error statistics presented in terms of Mean absolute error (MAE) and root-mean-square error (RMSIE). The results show that the spatial temperature distribution formed by IDS, OK and CK show similarity in general while the CK method better reflects the temperature distribution. Moreover, the best result for temperature mapping is obtained using the mixed method, which suggests that the correction of regression models using residuals improves the interpolation accuracy. Reliable calculation for agricultural management and improvement of climatic models at local scales can be obtained with increased efficiency.
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