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Comparison Study on the Estimation Algorithm of Land Surface Temperature for MODIS Data at the Korean Peninsula

MODIS 자료를 이용한 한반도 지표면 온도산출 알고리즘의 비교 연구

  • Lee, Soon-Hwan (BK21 Coastal Environment System School, Pusan National University) ;
  • Ahn, Ji-Suk (Department of Environmental Conservation and Disaster Prevention, Keimyung University) ;
  • Kim, Hae-Dong (Department of Environmental Conservation and Disaster Prevention, Keimyung University) ;
  • Hwang, Soo-Jin (Division of Science Education, Pusan National University)
  • 이순환 (부산대학교 BK21 연안환경시스템연구사업단) ;
  • 안지숙 (계명대학교 환경방제시스템학과) ;
  • 김해동 (계명대학교 환경방제시스템학과) ;
  • 황수진 (부산대학교 과학교육학부)
  • Published : 2009.04.30

Abstract

Comparison study on the land surface temperatures, which are calculated from four different algorithms for MODIS data, was carried out and the characteristics of each algorithm on land surface temperature estimation were also analysed in this study. Algorithms, which are well used for various satellite data analysis, in the comparisons are proposed by Price, Becker and Li, Ulivieri et al., and Wan. Verification of estimated land surface temperature from each algorithm is also performed using observation based regression data. The coefficient of determination ($R^2$) for daytime land surface temperature estimated from Wan's algorithm is higher than that of another algorithms at all seasons and the value of $R^2$ reach on 0.92 at spring. Although $R^2$ for Ulivieri's algorithm is slightly lower than that for Wan's algorithm, the variation pattern of land surface temperature for two algorithms are similar. However, the difference of estimated values among four algorithms become small at the region of high land surface temperature.

Keywords

References

  1. Ichinose T., Shimonodozono K., Hanaki K., 1999, Impact of anthropogenic heat on urban climate in Tokyo, Atmos. Environ., 33, 3897-3909 https://doi.org/10.1016/S1352-2310(99)00132-6
  2. 이순환, 이화운, 김유근, 2002, 복합지형에서 도시화에 따른 대기오염확산에 관한 시뮬레이션, 한국대기환경학회지, 18(2), 67-83
  3. 김해동, 이송옥, 구현숙, 2003, 대규모 주택단지내의 인공구조물에 의한 승온화 효과에 관한 연구, 한국환경과학회, 12(7), 705-71 https://doi.org/10.5322/JES.2003.12.7.705
  4. Mikami T., 2005, Urban Abnormal Climate of Tokyo, Yosen sha press, 95
  5. 이용식, 1990, 도시열섬 분석에 있어서 원격탐사 기법의 적용에 관한 연구, 석사학위논문, 환경계획학과, 서울대학교, 서울
  6. 박인환, 장갑수, 김종용, 1999, 추이대를 중심으로 한 경상북도 3개 도시열섬평가, 한국환경평가학회, 8(2), 73-82
  7. 조명희, 이광재, 김운수, 2001, 위성탐사자료와 GIS를 활용한 도시표면 온도의 공간적 분포 특성에 관한 연구, 한국지리정보학회, 4(1), 56-65
  8. 박민호, 2001, LANDSAT TM 열적외 데이터를 이용한 도시열섬현상에 관한 연구 - 서울시를 대상으로 -, 대한토목학회논문집, 21(6), 861-874
  9. 김해동, 임진욱, 이순환, 2006, 위성 자료를 이용한 대구광역시의 상대적 증발산 효율 분포, 한국환경과학회지, 27(6), 677-686
  10. Vogt J. V., Viau A. A., Paquet F., 1997, Mapping regional air temperature fields using satellite drived surface skin temperature, lnt. J. Climate, 17, 1559- 1579 https://doi.org/10.1002/(SICI)1097-0088(19971130)17:14<1559::AID-JOC211>3.0.CO;2-5
  11. 김해동, 2001, 우포늪이 주변 기후환경완화에 미치는 효과, 환경과학논집, 6(1), 99-106
  12. Han K. S., Viau A. A., Anctil F., 2003, High resolution forest fire weather index computations using satellite remote sensing, Can. J. Forest Res., 33, 1134-1143 https://doi.org/10.1139/x03-014
  13. 변민정, 한경수, 김영섭, 2004, 위성자료를 이용한 일 최고온도 산출의 통계적 접근에 관한 고찰, 한국원격탐사학회, 20(2), 65-76 https://doi.org/10.7780/kjrs.2004.20.2.65
  14. Ha K. J., Og H. M., Kim K. Y., 2001, Inter-annual and intra annual variabilities of NDVI, LAI, and Ts estimated by AVHRR in Korea, Korean J. Remote Sens., 17(2), 111-119
  15. 경기개발연구원, 2002, 아리랑1호(KOMPSAT-1) 위성영상 자료체계 구축 및 방안, 경기개발연구원보, 24-26
  16. 염종민, 한경수, 김영섭, 2005, 한반도 식생에 대한 MOIDS 250m 자료의 BRDF효과에 대한 반사도 정규화, 한국원격탐사학회지, 21(6), 445-456 https://doi.org/10.7780/kjrs.2005.21.6.445
  17. Wan Z., Zhang Y., Zhang 0., Li Z. L., 2002, Validation of the land-surface temperature products 367 retrieved from Terra Moderate Resolution Imaging Spectroradiometer data, Remote Sens. Environ., 83, 163-180 https://doi.org/10.1016/S0034-4257(02)00093-7
  18. Wan Z., Zhang Y, Zhang Q., Li Z. L., 2004, Quality assessment and validation of the MODIS global land-surface temperature, Int. J. Remote Sens., 25(1), 261-274 https://doi.org/10.1080/0143116031000116417
  19. Li Z. L, Jia L., Wan Z., Zhang R., 2003, A new approch for retrieving precipitable water from ATSR-2 split-window channel data over land area, In. J. Remote Sens., 24(24), 5095-5117 https://doi.org/10.1080/0143116031000096014
  20. Price J. c., 1984, Land surface temperature measurements from the split window channels of the NOAA-7 Advanced Very High Resolution Radiometer, Journal of Geophysical Research, 89, 7231-3237 https://doi.org/10.1029/JD089iD05p07231
  21. Becker F., Li Z. L., 1990, Toward a local split window method over land surface, Int. J. Remote Sens., II (3), 369-393 https://doi.org/10.1080/01431169008955028
  22. Ulivieri c., Castronouvo M. M., Francioni R., Cardillo A., 1994, A split-window algorithm for estimating land surface temperature from satellites, Advances in Space Research, 14(3), 59-65 https://doi.org/10.1016/0273-1177(94)90193-7
  23. 김소희, 2006, 기상위성자료를 이용한 지표면온도 산출 알고리즘의 상호비교, 석사학위논문, 대기과학과, 공주대학교, 공주
  24. Wan Z., 2003, Land surface temperature products users' guide, Technical report, Institute for Computational Earth System Science, University of California, Santa Barbara

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