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http://dx.doi.org/10.5532/KJAFM.2022.24.2.124

Comparative analysis of spatial interpolation methods of PM10 observation data in South Korea  

Kang, Jung-Hyuk (National Center for AgroMeteorology)
Lee, Seoyeon (National Center for AgroMeteorology)
Lee, Seung-Jae (National Center for AgroMeteorology)
Lee, Jae-Han (National Horticultural and Herbal Science)
Publication Information
Korean Journal of Agricultural and Forest Meteorology / v.24, no.2, 2022 , pp. 124-132 More about this Journal
Abstract
This study was aimed to visualize the spatial distribution of PM10 data measured at non-uniformly distributed observation sites in South Korea. Different spatial interpolation methods were applied to irregularly distributed PM10 observation data from January, 2019, when the concentration was the highest and in July, 2019, when the concentration was the lowest. Four interpolation methods with different parameters were used: Inverse Distance Weighted (IDW), Ordinary Kriging (OK), radial base function, and scattered interpolation. Six cases were cross-validated and the normalized root-mean-square error for each case was compared. The results showed that IDW using smoothing-related factors was the most appropriate method, while the OK method was least appropriate. Our results are expected to help users select the proper spatial interpolation method for PM10 data analysis with comparative reliability and effectiveness.
Keywords
$PM_{10}$; Spatial interpolation; Inverse distance weighted; Ordinary kriging; Radial base function; Scattered interpolation;
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