DOI QR코드

DOI QR Code

3차원 GIS 정합 및 투영에 기반한 사용자 친화적 레이더 자료 표출 기법

High-Precision and 3D GIS Matching and Projection Based User-Friendly Radar Display Technique

  • 장봉주 (한국건설기술연구원 수자원연구실) ;
  • 이건행 (한국건설기술연구원 수자원연구실) ;
  • 이동률 (한국건설기술연구원 수자원연구실) ;
  • 임상훈 (한국건설기술연구원 수자원연구실)
  • Jang, Bong-Joo (Water Resources Research Division, Korea Institute of Civil Engineering and Building Technology) ;
  • Lee, Keon-Haeng (Water Resources Research Division, Korea Institute of Civil Engineering and Building Technology) ;
  • Lee, Dong-Ryul (Water Resources Research Division, Korea Institute of Civil Engineering and Building Technology) ;
  • Lim, Sanghun (Water Resources Research Division, Korea Institute of Civil Engineering and Building Technology)
  • 투고 : 2014.08.14
  • 심사 : 2014.11.05
  • 발행 : 2014.12.31

초록

최근, 기상레이더는 돌발적 기상재해들을 예방하고, 기상관측의 공익을 위해 널리 이용되고 있으며 이에 따라 사용자 관점의 레이더 표출 시스템의 필요성이 대두되고 있다. 본 논문은 레이더 관측 자료들을 멀티미디어 콘텐츠로서 재생산하는 방법과 생성된 자료를 이용해 매쉬업 서비스에 적용하는 방법을 제안하였다. 이와 함께 주요 기상현상이 발생중인 지역의 정확한 위치를 추적하기 위한 정밀 GIS 정합기술을 제안하였다. 본 연구에서 제시하는 방법을 통해 기상 레이더로부터 관측된 다양한 레이더 변수들을 재가공함으로써 2차원의 영상 및 벡터 그래픽 자료, 또는 3차원 볼륨 자료 등을 생성할 수 있다. 생성된 멀티미디어 형태의 레이더 자료들은 다양한 래스터 또는 벡터정밀 GIS 맵과 정합된다. 다양한 강수 시나리오에 대한 실험 결과, 제안한 방법에 의한 표출 시스템은 사용자로 하여금 정확한 레이더 차폐영역 분석, 강수이동경로 파악, 강수량 추정에 따른 홍수위험도 분석 등을 쉽고 직관적으로 이해시킬 수 있음을 확인하였다. 제안하는 정밀한 GIS 정합을 통해 재난 관리자가 레이더 관측자료를 명확히 해석하고 이를 통해 보다 효과적인 기상재해 예보가 가능할 것으로 기대한다.

In recent years, as frequency and intensity of severe weather disasters such as flash flood have been increasing, providing accurate and prompt information to the public is very important and needs of user-friendly monitoring/warning system are growing. This paper introduces a method that re-produces radar observations as multimedia contents and applies reproduced data to mesh-up services. In addition, a accurate GIS matching technique to help to track the exact location going on serious atmospheric phenomena is presented. The proposed method create multimedia contents having structures such as two dimensional images, vector graphics or three dimensional volume data by re-producing various radar variables obtained from a weather radar. After then, the multimedia formatted weather radar data are matched with various detailed raster or vector GIS map platform. Results of simulation test with various scenarios indicate that the display system based on the proposed method can support for users to figure out easily and intuitively routes and degrees of risk of severe weather. We expect that this technique can also help for emergency manager to interpret radar observations properly and to forecast meteorological disasters more effectively.

키워드

참고문헌

  1. Bringi, V.N., and Chandrasekar, V. (2001). "Polarimetric Doppler Weather Radar: Principles and Applications." Cambridge University Press, New York, NY.
  2. Chandrasekar, V., Wang, Y., Lim, S., and Francesc, J. (2011). "Accomplishments, challenges and opportunities in developing network based radar systems for high-impact small-scale weather events." Radar Conference (RADAR), IEEE, pp. 1056-1061.
  3. Google, http://www.google.com/earth/index.html, Retrieve June, 5 2014.
  4. HRFCO(Han River Flood Control Office), http://www.hrfco.go.kr/html/flood/realTime_4.jsp, Retrieved Oct., 29 2014.
  5. Hu, H. (2014). "An algorithm for converting weather radar data into GIS polygons and its application in severe weather warning systems." International Journal of Geographical Information Science, Vol. 28, No. 9, pp. 1765-1780. https://doi.org/10.1080/13658816.2014.898767
  6. James, C.N, Brodzik, S.R., Edmon, H., Houze Jr, R.A., and Yuter, S.E. (2000). "Radar data processing and visualization over complex terrain." Weather and Forecasting, Vol. 15, No. 3, pp. 327-338. https://doi.org/10.1175/1520-0434(2000)015<0327:RDPAVO>2.0.CO;2
  7. Jang, B.-J., Lim, S., Lee, S.-H., Moon, K.-S., Chandrasekar, V., and Kwon, K.-R. (2013). "A visualization method of high definition weather radar information for various GIS platform." Journal of Korea Multimedia Society, Vol. 16, No. 11, pp. 1239-1245. https://doi.org/10.9717/kmms.2013.16.11.1239
  8. KMA(Korea Meteorological Administration), http://www.kma.go.kr/weather/images/rader_composite_cappi.jsp, Retrieved Oct., 29 2014.
  9. Lim, S., Chandrasekar, V., and Bringi, V.N. (2005). "Hydrometeor classification system using dual-polarization radar measurements: Model improvements and in situ verification." Geoscience and Remote Sensing, IEEE Transactions on, Vol. 43, No. 4, pp. 792-801. https://doi.org/10.1109/TGRS.2004.843077
  10. Mcgill University, http://www.radar.mcgill.ca/, Retrieved June, 11 2014.
  11. Wernecke, J. (2008). The KML Handbook: Geographic Visualization for theWeb. Addison-Wesley Professional. p368.
  12. Xie, H., Zhou, X., Vivoni, E.R., Hendrickx, J.M.H., and Small, E.E. (2005). "GIS-based NEXRAD Stage III precipitation database: automated approaches for data processing and visualization." Computers & Geosciences, Vol. 31, No. 1, pp. 65-76. https://doi.org/10.1016/j.cageo.2004.09.009
  13. You, C.-H, Lee, G.-W., and Han, H.-Y. (2012). "Radar data quality control algorithm for KMA weather radar center." Journal of Korea Water Resources Association, Vol. 45, No. 8, pp. 44-49.

피인용 문헌

  1. Study about Real-time Total Monitoring Technique for Various Kinds of Multi Weather Radar Data vol.19, pp.4, 2016, https://doi.org/10.9717/kmms.2016.19.4.689
  2. Hierarchical Compression Technique for Reflectivity Data of Weather Radar vol.18, pp.7, 2015, https://doi.org/10.9717/kmms.2015.18.7.793
  3. A Plan for a Prompt Disaster Response System Using a 3D Disaster Management System Based on High-Capacity Geographic and Disaster Information vol.19, pp.1, 2016, https://doi.org/10.11108/kagis.2016.19.1.180
  4. Study about Road-Surrounding Environment Analysis and Monitoring Platform based on Multiple Vehicle Sensors vol.19, pp.8, 2016, https://doi.org/10.9717/kmms.2016.19.8.1505
  5. A Study on the Construction of the Unity 3D Engine Based on the WebGIS System for the Hydrological and Water Hazard Information Display vol.154, 2016, https://doi.org/10.1016/j.proeng.2016.07.431