Korean Journal of Agricultural and Forest Meteorology (한국농림기상학회지)

Korean Society of Agricultural and Forest Meteorology (한국농림기상학회)
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Python Package Production for Agricultural Researcher to Use Meteorological Data

농업연구자의 기상자료 활용을 위한 파이썬 패키지 제작

  • Hyeon Ji Yang (EPINET Co., Ltd.) ;
  • Joo Hyun Park (EPINET Co., Ltd.) ;
  • Mun-Il Ahn (EPINET Co., Ltd.) ;
  • Min Gu Kang (Pnational Institute of Agricultural Sciences, RDA) ;
  • Yong Kyu Han (EPINET Co., Ltd.) ;
  • Eun Woo Park (EPINET Co., Ltd.)
  • 양현지 (에피넷) ;
  • 박주현 (에피넷) ;
  • 안문일 (에피넷) ;
  • 강민구 (국립농업과학원) ;
  • 한용규 (에피넷) ;
  • 박은우 (에피넷)
  • Received : 2022.11.03
  • Accepted : 2023.04.05
  • Published : 2023.06.30
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Abstract

Recently, the abnormal weather events and crop damages occurred frequently likely due to climate change. The importance of meteorological data in agricultural research is increasing. Researchers can download weather observation data by accessing the websites provided by the KMA (Korea Meteorological Administration) and the RDA (Rural Development Administration). However, there is a disadvantage that multiple inquiry work is required when a large amount of meteorological data needs to be received. It is inefficient for each researcher to store and manage the data needed for research on an independent local computer in order to avoid this work. In addition, even if all the data were downloaded, additional work is required to find and open several files for research. In this study, data collected by the KMA and RDA were uploaded to GitHub, a remote storage service, and a package was created that allows easy access to weather data using Python. Through this, we propose a method to increase the accessibility and usability of meteorological data for agricultural personnel by adopting a method that allows anyone to take data without an additional authentication process.

농업은 기상에 매우 민감한 산업으로, 따라서 농업분야의 기상을 이용한 연구는 더욱 중요해지고 있다. 연구자들은 기상청과 농촌진흥청에서 제공하는 기상정보서비스 웹사이트에 접속해 기상관측자료를 다운로드할 수 있다. 그러나 대량의 기상자료를 받아야 할 때는 여러 번의 조회작업이 필요한 단점이 있다. 본 데이터 논문은 기상청과 농촌진흥청에서 수집한 자료를 원격 저장소 서비스인 깃허브에 업로드하고 소프트웨어 프로그램인 파이썬을 이용해 기상자료에 쉽게 접근할 수 있는 패키지를 제작했다. 이를 통해 추가적인 인증 절차 없이 누구나 자료를 가져갈 수 있는 방식을 채택하여 농업 관계자들의 기상자료에 대한 접근성 및 활용성을 높이는 방법을 제안한다. 자료와 패키지는 분산 버전 관리 시스템인 깃에 업로드하여 수정 및 관리가 용이하게 하였다.

Keywords

Acknowledgement

본 연구는 농촌진흥청 국립농업과학원 농업과학기술 연구개발사업 (과제번호: PJ0148942022)의 지원에 의해 수행되었음.

References

  1. Cho, Y. N., C. Y. Yoon, H. K. Kim, H. D. Moon, K. N. An, and J. I. Cho, 2020: Meteorological data measured under Agrivoltaic Systems in Boseong-gun during winter barley season. Korean Journal of Agricultural and Forest Meteorology 22(3), 144-151. (in Korean with English abstract)
  2. Hur, J. N., J. H. Park, K. M. Shim, Y. S. Kim, and S. R. Jo, 2020: A high-resolution agro-climatic dataset for assessment of climate change over South Korea. Korean Journal of Agricultural and Forest Meteorology 22(3), 128-134. (in Korean with English abstract)
  3. Jang, Y. B., I. H. Jang, and Y. C. Choe, 2020: Prediction of soil moisture with open source weather data and machine learning algorithms. Korean Journal of Agricultural and Forest Meteorology 22(1), 1-12. (in Korean with English abstract)
  4. Jeong, H. K., J. H. Sung, and H. J. Lee, 2020: Analysis of Social Demand for Countermeasures in Response to Extreme Weather Events in Korean Agricultural Sector. Journal of Climate Change Research 11(4), 235-246. (in Korean with English abstract) https://doi.org/10.15531/KSCCR.2020.11.4.235
  5. Kang, H. S., J. H. Cho, and H. C. Kim, 2017: Case Study on Software Education using Social Coding Sites. Journal of Digital Convergence 15(5), 37-48. (in Korean with English abstract) https://doi.org/10.14400/JDC.2017.15.5.37
  6. Kim, H. K. H. D. Moon, Y. N. Cho, S. H. Sin, J. H. Kim, Y. W. Lee, and J. I. Cho, 2021: Direct and Diffuse Radiation Data in Naju During May 2019 to November 2020. Korean Journal of Agricultural and Forest Meteorology 23(2), 134-140. (in Korean with English abstract)
  7. Korea Meteorological Administration (KMA), 2017: Abnormal Climate Report 2016. KMA, 58pp. (in Korean)
  8. Korea Meteorological Administration (KMA), 2021: Abnormal Climate Report 2020. KMA, 78-81. (in Korean)
  9. Korea Meteorological Administration (KMA), 2022: Abnormal Climate Report 2021. KMA, 78-80. (in Korean)
  10. Lee, J. H., 2016: 공학적 데이터 처리를 위한 파이썬 (Python) 언어의 활용: Spyder (Scientific PYthon Development EnviRonment). The Korean Institute of Electrical Engineers 65(5), 41-48. https://doi.org/10.5370/KIEEP.2016.65.1.041
  11. Lee, S. H., and I. Y. Lee, 2011: Effective Searchable Symmetric Encryption System using Conjunctive Keyword on Remote Storage Environment. The KIPS Transactions:PartC 18C(4), 199-206. https://doi.org/10.3745/KIPSTC.2011.18C.4.199
  12. Noh, H. J., and J. H. Son, 2021: 오픈 API 기반의 금융생태계 변화와 시사점. KIRI report(포커스). 521, 8-13.
  13. Park, J. H., Y. S. Shin, and K. M. Shim, 2021: Improvements of Unit System for nationwide expansion of Early Warning Service for Agrometeorological Disaster. Korean Journal of Agricultural and Forest Meteorology 23(4), 356-365. (in Korean with English abstract)
  14. Shim, K. M., Y. S. Kim, M. P. Jung, J. W. Kim, M. S. Park, S. H. Hong, and K. K. Kang, 2018: Recent Changes in the Frequency of Occurrence of Extreme Weather Events in South Korea. Journal of Climate Change Research 9(4), 461-470. (in Korean with English abstract) https://doi.org/10.15531/KSCCR.2018.9.4.461
  15. Version control, 2021: https://en.wikipedia.org/wiki/Version_control (2021. 4. 15. Accessed)