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A comparison of spatial interpolation methods to estimate continuous wind speed surfaces using irregularly distributed data from England and Wales
Author(s) -
Luo W.,
Taylor M. C.,
Parker S. R.
Publication year - 2007
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.1583
Subject(s) - multivariate interpolation , interpolation (computer graphics) , robustness (evolution) , kriging , wind speed , statistics , meteorology , spatial distribution , computer science , mathematics , environmental science , remote sensing , bilinear interpolation , geography , artificial intelligence , motion (physics) , biochemistry , chemistry , gene
Seven methods of spatial interpolation were compared to determine their suitability for estimating daily mean wind speed surfaces, from data recorded at nearly 190 locations across England and Wales. The eventual purpose of producing such surfaces is to help estimate the daily spread of pathogens causing crop diseases as they move across regions. The interpolation techniques included four deterministic and three geostatistical methods. Quantitative assessment of the continuous surfaces showed that there was a large difference between the accuracy of the seven interpolation methods and that the geostatistical methods were superior to deterministic methods. Further analyses, testing the reliability of the results, showed that measurement accuracy, density, distribution and spatial variability had a substantial influence on the accuracy of the interpolation methods. Independent wind speed data from ten other dates were used to confirm the robustness of the best interpolation methods. © Crown copyright 2007. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd.

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