Korean Journal of Agricultural and Forest Meteorology (한국농림기상학회지)

Korean Society of Agricultural and Forest Meteorology (한국농림기상학회)
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Comparative analysis of spatial interpolation methods of PM10 observation data in South Korea

남한지역 PM10 관측자료의 공간 보간법에 대한 비교 분석

  • Received : 2021.11.15
  • Accepted : 2022.06.02
  • Published : 2022.06.30
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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.

불균일한 미세먼지 관측값으로부터 남한 전체에 대한 공간적 분포를 추정하기 위해서는 적절한 보간 처리가 필수이다. 본 연구에서는 2019년도에 미세먼지 농도가 높았던 1월달과 농도가 낮았던 7월달의 전국의 기상청 및 AirKorea 측정소 자료를 이용하여 IDW, OK, SI, RBF 총 4가지 보간법을 테스트하였다. 각 보간 방법별 세부 인자를 고려한 총 6가지 경우에 대해 보간 처리 및 교차 검증을 진행하였다. 자료 처리속도는 SI, RBF, IDW, OK 순으로 빠르게 나타났다. 교차 검증의 결과, IDW가 상대적으로 제일 낮은 NRMSE 결과를 보였고 OK방법이 가장 큰 NRMSE를 보였다. 이러한 연구의 결과는 사용자가 남한 지역에서 불균일한 미세먼지 관측 자료를 사용하여 전체 수평 공간을 보간할 때 적합한 방법을 단기간에 선택하고 신뢰성과 효과성 있는 분석을 실시하는데 도움이 될 것으로 기대된다.

Keywords

Acknowledgement

본 연구는 농촌진흥청 연구사업 '미세먼지에 의한 농작물 생산피해 예측 및 평가기술 개발'(세부과제번호: PJ014189032021)의 지원을 받아 이루어진 것입니다.

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