DOI QR코드

DOI QR Code

Inter-comparison of three land surface emissivity data sets (MODIS, CIMSS, KNU) in the Asian-Oceanian regions

아시아-오세아니아 지역에서의 세 지표면 방출률 자료 (MODIS, CIMSS, KNU) 상호비교

  • Park, Ki-Hong (Department of Atmospheric Science, Kongju National University) ;
  • Suh, Myoung-Seok (Department of Atmospheric Science, Kongju National University)
  • Received : 2013.04.09
  • Accepted : 2013.04.22
  • Published : 2013.04.30

Abstract

In this study, spatio-temporal variations of Land Surface Emissivity (LSE) of the three LSE data sets in the Asian-Oceanian regions were addressed. The MODerate Resolution Imaging Spectroradiometer (MODIS) LSE, Cooperative Institute for Meteorological Satellite Studies (CIMSS) LSE, and Kongju National Univ. (KNU) LSE data sets were used. The three data sets showed very similar emissivity in the Tibetan Plateau, desert in the Middle East and Australia, and low latitude regions irrespective of season. The emissivity of $12{\mu}m$ was systematically greater than that of $11{\mu}m$, in particular, in the Tibetan Plateau, desert over Middle East and Australia. In general, they showed a weak seasonal variation in the low latitude regions although the emissivity was different among them. However, the three data sets showed quite different spatial and temporal variations in the other regions of Asian-Oceanian regions. The KNU LSE showed a systematic seasonal variation with a high emissivity during summer and low emissivity during winter but the other two LSE data sets showed irregular seasonal variations without regard to the regions. And the annual mean correlations of $11{\mu}m$ and $12{\mu}m$ between KNU LSE and MODIS LSE (KNU LSE and CIMSS LSE; MODIS LSE and CIMSS LSE) were 0.423 and 0.399 (0.330, 0.101; 0.541, 0.154), respectively. The relatively low correlations and strong inter-month variations, in particular, in $12{\mu}m$, indicated that consistency in spatial variation was very low. The comparison results showed that caution should be given before operational use of the LSE data sets in these regions.

본 연구에서는 아시아-오세아니아 지역에서의 세 지표면 방출률 자료 (MODIS, CIMSS, KNU)의 시 공간적 분포와 변동 특성을 비교 분석하였다. 세 자료 모두 계절에 관계없이 티베트 고원, 페르시아만 주변의 중동지역 및 호주 사막지역, 저위도 지역에서 매우 유사한 방출률 분포를 보이고 있다. 일부지역을 제외한 대부분 지역에서 $12{\mu}m$ 채널의 방출률이 $11{\mu}m$보다 크며, 특히 티베트 고원과 중동지역, 호주 사막지역 일부에서 그 차이가 크다. 저위도 지역에서의 방출률은 서로 상이하지만 방출률의 계절변동이 크지 않은 공통점을 보이고 있다. 그러나 그 외 대부분 지역에서 세 자료는 방출률의 시 공간 변동성에서 큰 차이를 보이고 있다. KNU 자료는 여름에 높고 겨울에 낮은 방출률을 보여 계절변동이 뚜렷하나, MODIS와 CIMSS 자료는 계절에 따른 방출률 변화가 불규칙하며 뚜렷하지 않았다. KNU와 MODIS(KNU와 CIMSS; MODIS와 CIMSS) 자료간의 공간상관계수의 연평균은 $11{\mu}m$$12{\mu}m$ 채널에서 각각 0.423과 0.399 (0.330, 0.101; 0.541, 0.154)로 낮다. 특히 $12{\mu}m$ 채널의 경우 서로 상관성이 매우 낮을 뿐만 아니라 상관계수의 월 변동도 강하게 나타나 세 자료간 일치성이 매우 낮다. 본 연구 결과는 아시아-오세아니아 지역에서의 지표면 방출률 자료 개선이 시급함을 제시한다.

Keywords

References

  1. Becker, F., and Z.L. Li, 1990. Temperature-independent spectral indices in thermal infrared bands, Remote Sensing of Environment, 32: 17-33. https://doi.org/10.1016/0034-4257(90)90095-4
  2. Gillespie, A.R., S. Rokugawa, S.J. Hook, T. Matsunaga, and A.B. Hahle, 1999. Temperature/emissivity separation algorithm theoretical basis document, version 2.4, NAS5-31372, NASA/GSFC, Greenbelt, MD, USA.
  3. Hong, K.-O., M.-S. Suh, and J.-H. Kang, 2009. Improvement of COMS Land Surface Temperature Retrieval Algorithm, Korean Journal of Remote Sensing, 25(6): 1-10. https://doi.org/10.7780/kjrs.2009.25.6.507
  4. Hulley, G.C., and S.J. Hook, 2009. Intercomparison of versions 4, 4.1 and 5 of the MODIS Land Surface Temperature and Emissivity products and validation with laboratory measurements of sand samples from the Namib desert, Namibia, Remote Sensing of Environment, 113(6): 1313-1318. https://doi.org/10.1016/j.rse.2009.02.018
  5. Jiang, G.-M., Z.-L. Li, and F. Nerry, 2006. Land surface emissivity retrieval from combined mid-infrared and thermal infrared data of MSG-SEVIRI, Remote Sensing of Environment, 105(4): 326-340. https://doi.org/10.1016/j.rse.2006.07.015
  6. Kahle, A.B., D.P. Madura, and J.M. Soha, 1980. Middle infrared multispectral aircraft scanner data: analysis for geological applications, Applied Optics, 19: 2279-2290. https://doi.org/10.1364/AO.19.002279
  7. Kang, J.-H., M.-S., Suh and C.-H. Kwak, 2007. A Comparison of the Land Cover Data Sets over Asian Region: USGS, IGBP, and UMd, Atmosphere, 17(2): 159-169.
  8. Kealy, P.S., and A.R. Gabell, 1990. Estimation of emissivity and temperature using alpha coefficients, Proc. of the second Thermal Infrared Multispectral Scanner (TIMS) workshop, Pasadena, CA, Jun. 6, vol. 90-55, pp. 11-15.
  9. Kealy, P.S., and S.J. Hook, 1993. Separating temperature and emissivity in thermal infrared multispectral scanner data: Implications for recovering land surface temperatures, IEEE Transactions on Geoscience and Remote Sensing, 31: 1155-1164. https://doi.org/10.1109/36.317447
  10. Kerr, Y.H., J.P. Lagouarde, and J. Imbernon, 1992. Accurate land surface temperature retrieval from AVHRR data with use of an improved split window algorithm, Remote Sensing of Environment, 41: 197-209. https://doi.org/10.1016/0034-4257(92)90078-X
  11. Korea Meteorological Administration, 2009. Development of retrieval and application algorithms for land surface information from satellite data, pp. 58-95.
  12. Kornfield, J., and J. Susskind, 1977. On the effect of surface emissivity on temperature retrievals, Monthly Weather Review, 105(12): 1605-1608. https://doi.org/10.1175/1520-0493(1977)105<1605:OTEOSE>2.0.CO;2
  13. Li, Z., J. Li, X. Jin, T.J. Schmit, E.E. Borbas, and M.D. Goldberg, 2010. An objective methodology for infrared land surface emissivity evaluation, Journal of Geophysical Research, 115(D22), doi:10.1029/2010JD014249.
  14. Peres, L.F., and C.C. DaCamara, 2005. Emissivity maps to retrieve land-surface temperature from MSG/SEVIRI, IEEE Transactions on Geoscience and Remote Sensing, 43(8): 1834-1844. https://doi.org/10.1109/TGRS.2005.851172
  15. Seemann, S.W., E.E. Borbas, R.O. Knuteson, G.R. Stephenson, and H.-L. Huang, 2008. Development of a Global Infrared Land Surface Emissivity Database for Application to Clear Sky Sounding Retrievals from Multi-spectral Satellite Radiance Measurements, Journal of Applied Meteorology and Climatology, 47: 108-123. https://doi.org/10.1175/2007JAMC1590.1
  16. Snyder, W.C., and Z. Wan, 1998. BRDF models to predict spectral reflectance and emissivity in the thermal infrared, IEEE Transactions on Geoscience and Remote Sensing, 36: 214-225. https://doi.org/10.1109/36.655331
  17. Snyder, W.C., Z. Wan, Y. Zhang, and Y.Z. Feng, 1998. Classification-based emissivity for land surface temperature measurement from space, International Journal of Remote Sensing, 19: 2753-2774. https://doi.org/10.1080/014311698214497
  18. Sobrino, J.A., J.C. Jimenez-Munoz, G. Soria, M. Romaguera, L. Guanter, J. Moreno, A. Plaza, and P. Martinez, 2008. Land Surface Emissivity Retrieval From Different VNIR and TIR Sensors, IEEE Transactions on Geoscience and Remote Sensing, 46(2): 316-327. https://doi.org/10.1109/TGRS.2007.904834
  19. Suh, M.-S., S.-H. Kim, and J.-H. Kang, 2008. A comparative study of algorithms for estimating land surface temperature from MODIS data, Korean Journal of Remote Sensing, 24: 65-78. https://doi.org/10.7780/kjrs.2008.24.1.65
  20. Valor, E., and V. Caselles, 1996. Mapping land surface emissivity from NDVI: Application to European, African, and South American areas, Remote Sensing of Environment, 57: 164-184.
  21. Wan, Z., 2008. New refinements and validation of the MODIS land-surface temperature/emissivity products, Remote Sensing of Environment, 112: 59-74. https://doi.org/10.1016/j.rse.2006.06.026

Cited by

  1. Evaluation of Land Surface Temperature Operationally Retrieved from Korean Geostationary Satellite (COMS) Data vol.5, pp.8, 2013, https://doi.org/10.3390/rs5083951
  2. Improvement of infrared channel emissivity data in COMS observation area from recent MODIS data(2009-2012) vol.30, pp.1, 2014, https://doi.org/10.7780/kjrs.2014.30.1.9
  3. Retrieval of Fire Radiative Power from Himawari-8 Satellite Data Using the Mid-Infrared Radiance Method vol.24, pp.4, 2016, https://doi.org/10.7319/kogsis.2016.24.4.105
  4. LANDSAT 영상을 이용한 세종특별자치시의 도시화와 열섬현상 분석 vol.34, pp.3, 2013, https://doi.org/10.12652/ksce.2014.34.3.1033
  5. 다중선형회귀모형에 의한 지표면 광대역 방출율 산출 vol.38, pp.4, 2013, https://doi.org/10.5467/jkess.2017.38.4.269
  6. 서울시 주요 공원, 유적지 및 공공기관시설 내 연못 및 호수면적 변화에 따른 LST(Land Surface Temperature) 분포 경향 - 다중시기의 Landsat TM/ETM 위성영상을 이용하여 vol.17, pp.6, 2013, https://doi.org/10.12813/kieae.2017.17.6.063