Abstract
This study aims to provide a comparative analysis of two of the most used methods of spatial interpolation – Thiessen Polygons (TP) and Inverse Distance Weighting (IDW) with a spatio-temporal approach – Spatio-temporal kriging (STK) on a data series from Canada. The IDW parameter is optimized to obtain the best fitting for the studied series, based on the Root Mean Squared Errors (RMSE) and Mean Absolute Percentage Error (MAPE). The advantages and disadvantages of each algorithm are emphasized. Although TP registered the lowest RMSE and a MAPE, the analysis favors the STK use for modeling Montreal’s maximum temperature series.
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