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http://dx.doi.org/10.7780/kjrs.2021.37.3.2

Kriging of Daily PM10 Concentration from the Air Korea Stations Nationwide and the Accuracy Assessment  

Jeong, Yemin (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Cho, Subin (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Youn, Youjeong (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Kim, Seoyeon (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Kim, Geunah (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Kang, Jonggu (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Lee, Dalgeun (Disaster Information Research Division, National Disaster Management Research Institute)
Chung, Euk (Disaster Information Research Division, National Disaster Management Research Institute)
Lee, Yangwon (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.37, no.3, 2021 , pp. 379-394 More about this Journal
Abstract
Air pollution data in South Korea is provided on a real-time basis by Air Korea stations since 2005. Previous studies have shown the feasibility of gridding air pollution data, but they were confined to a few cities. This paper examines the creation of nationwide gridded maps for PM10 concentration using 333 Air Korea stations with variogram optimization and ordinary kriging. The accuracy of the spatial interpolation was evaluated by various sampling schemes to avoid a too dense or too sparse distribution of the validation points. Using the 114,745 matchups, a four-round blind test was conducted by extracting random validation points for every 365 days in 2019. The overall accuracy was stably high with the MAE of 5.697 ㎍/m3 and the CC of 0.947. Approximately 1,500 cases for high PM10 concentration also showed a result with the MAE of about 12 ㎍/m3 and the CC over 0.87, which means that the proposed method was effective and applicable to various situations. The gridded maps for daily PM10 concentration at the resolution of 0.05° also showed a reasonable spatial distribution, which can be used as an input variable for a gridded prediction of tomorrow's PM10 concentration.
Keywords
PM10; Kriging; Variogram; Interpolation accuracy;
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