DOI QR코드

DOI QR Code

Comparison of Land Surface Temperatures from Near-surface Measurement and Satellite-based Product

  • Ryu, Jae-Hyun (Department of Applied Plant Science, Chonnam National University) ;
  • Jeong, Hoejeong (Department of Applied Plant Science, Chonnam National University) ;
  • Choi, Seonwoong (Department of Applied Plant Science, Chonnam National University) ;
  • Lee, Yang-Won (Department of Spatial Information Engineering, Pukyong National University) ;
  • Cho, Jaeil (Department of Applied Plant Science, Chonnam National University)
  • Received : 2019.07.31
  • Accepted : 2019.08.20
  • Published : 2019.08.31

Abstract

Land surface temperature ($T_s$) is a critical variable for understanding the surface energy exchange between land and atmosphere. Using the data measured from micrometeorological flux towers, three types of $T_s$, obtained using a thermal-infrared radiometer (IRT), a net radiometer, and an equation for sensible heat flux, were compared. The $T_s$ estimated using the net radiometer was highly correlated with the $T_s$ obtained from the IRT. Both values acceptably fit the $T_s$ from the Terra/MODIS (Moderate Resolution Imaging Spectroradiometer)satellite. These results will enhance the measurement of land surface temperatures at various scales. Further, they are useful for understanding land surface energy partitioning to evaluate and develop land surface models and algorithms for satellite remote sensing products associated with surface thermal conditions.

Acknowledgement

Supported by : Korea Meteorological Administration

References

  1. Wan, Z. and Z.-L. Li, 2008. Radiance-based validation of the V5 MODIS land-surface temperature product, International Journal of Remote Sensing, 29(17-18): 5373-5395. https://doi.org/10.1080/01431160802036565
  2. Wan, Z., 2008. New refinements and validation of the MODIS land-surface temperature/emissivity products, Remote Sensing of Environment, 112(1): 59-74. https://doi.org/10.1016/j.rse.2006.06.026
  3. Dash, P., F.-M. Gottsche, F.-S. Olesen, and H. Fischer, 2002. Land surface temperature and emissivity estimation from passive sensor data: Theory and practice current trends, International Journal of Remote Sensing, 23(13): 2563-2594. https://doi.org/10.1080/01431160110115041
  4. Jin, M., 2004. Analysis of Land Skin Temperature Using AVHRR Observations, Bulletin of the American Meteorological Society, 85(4): 587-600. https://doi.org/10.1175/BAMS-85-4-587
  5. Baldocchi, D., E. Falge, L. Gu, R. Olson, D. Hollinger, S. Running, P. Anthoni, C. Bernhofer, K. Davis, R. Evans, J. Fuentes, A. Goldstein, G. Katul, B. Law, X. Lee, Y. Malhi, T. Meyers, W. Munger, W. Oechel, K.T. Paw U. K. Pilegaard, H.P. Schmid, R. Valentini, S. Verma, T. Vesala, K. Wilson, and S. Wofsy, 2001. FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities, Bulletin of the American Meteorological Society, 82(11): 2415-2434. https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2
  6. Coll, C., V. Caselles, J.M. Galve, E. Valor, R. Niclos, J.M. Sanchez, and R. Rivas, 2005. Ground measurements for the validation of land surface temperatures derived from AATSR and MODIS data, Remote Sensing of Environment, 97(3): 288-300. https://doi.org/10.1016/j.rse.2005.05.007
  7. Jones, H.G., R. Serraj, B.R. Loveys, L. Xiong, A. Wheaton, and A.H. Price, 2009. Thermal infrared imaging of crop canopies for the remote diagnosis and quantification of plant responses to water stress in the field, Functional Plant Biology, 36(11): 978-989. https://doi.org/10.1071/FP09123
  8. Li, Z. L., B.H. Tang, H. Wu, H. Ren, G. Yan, Z. Wan, I.F. Trigo, and J.A. Sobrino, 2013. Satellite-derived land surface temperature: Current status and perspectives, Remote Sensing of Environment, 131: 14-37. https://doi.org/10.1016/j.rse.2012.12.008
  9. Mildrexler, D.J., M. Zhao, M. Owe, and S.W. Running, 2011. A global comparison between station air temperatures and MODIS land surface temperatures reveals the cooling role of forests, Journal of Geophysical Research: Biogeosciences, 116: G03025.
  10. Park, K.-H. and M.-S. Suh, 2013. Inter-comparison of three land surface emissivity data sets (MODIS, CIMSS, KNU) in the Asian-Oceanian regions, Korean Journal of Remote Sensing, 29(2): 219-233 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2013.29.2.6
  11. Park, K.-H. and M.-S. Suh, 2014. Improvement of infrared channel emissivity data in COMS observation area from recent MODIS data (2009-2012), Korean Journal of Remote Sensing, 30(1): 109-126 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2014.30.1.9
  12. Prata, A.J., V. Caselles, C. Coll, J.A. Sobrino, and C. Ottle, 1995. Thermal remote sensing of land surface temperature from satellites: Current status and future prospects, Remote Sensing Reviews, 12(3-4): 175-224. https://doi.org/10.1080/02757259509532285
  13. Tang, B.H., K. Shao, Z.L. Li, H. Wu, F. Nerry, and G. Zhou, 2015. Estimation and validation of land surface temperatures from Chinese second-generation polar-orbit FY-3A VIRR data, Remote Sensing, 7(3): 3250-3273. https://doi.org/10.3390/rs70303250
  14. Trigo, I.F., I.T. Monteiro, F. Olesen, and E. Kabsch, 2008. An assessment of remotely sensed land surface temperature, Journal of Geophysical Research, 113: D17108. https://doi.org/10.1029/2008JD010035
  15. Voogt, J.A. and T.R. Oke, 2003. Thermal remote sensing of urban climates, Remote Sensing of Environment, 86(3): 370-384. https://doi.org/10.1016/S0034-4257(03)00079-8