MODIS Land Surface Temperature and Emissivity

  • Zhengming Wan
  • Zhao-Liang Li
Part of the Remote Sensing and Digital Image Processing book series (RDIP, volume 11)


Land surface temperature (LST) is a key parameter in the physics of land surface processes at regional and global scales, combining the results of all surface–­atmosphere interactions and energy fluxes between the atmosphere and the ground (Mannstein 1987; Sellers et al. 1988). The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua platforms produce high-quality LST products from data, which possess a number of strengths. They include global coverage, high radiometric resolution and wide dynamic ranges, accurate geolocation (Wolfe et al. 2002), and high-quality thermal infrared (TIR) calibration accuracy used in the LST retrieval (Barnes et al. 1998).


Normalize Difference Vegetation Index Land Surface Temperature Column Water Vapor MODIS Land Surface Temperature Land Surface Temperature Product 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by EOS Program contracts NAS5-31370 and NNG04HZ15C of the National Aeronautics and Space Administration. Dr. Li’s work is partly supported by China’s National Natural Science Foundation under Grant 40425012, and the “Hundred Talent” program of the Chinese Academy of Sciences. Larry Zangwill performed the spectral measurements of ivy leaf samples in the laboratory of the UCSB MODIS LST Group and participated in LST validation field campaigns.


  1. Barnes WL, Pagano TS, Salomonson VV (1998) Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1. IEEE Trans Geosci Remote Sens 36:1088–1100ADSCrossRefGoogle Scholar
  2. Becker F, Li Z-L (1990) Toward a local split-window method over land surface. Int J Remote Sens 3:369–393CrossRefGoogle Scholar
  3. Berk A, Anderson GP, Bernstein LS, Acharya PK, Dothe H, Matthew MW, Adler-Golden SM, Chetwynd JH Jr, Richtmeier SC, Pukall B, Allred CL, Jeong LS, Hoke ML (1999) MODTRAN4 radiative transfer modeling for atmospheric correction. Optical Spectroscopic Techniques and Instrumentation for Atmospheric and Space Research III. Proc SPIE 3756:348–353ADSCrossRefGoogle Scholar
  4. Coll C, Caselles V, Galve JM, Valor E, Niclòs R, Sánchez JM, Rivas R (2005) Ground measurements for the validation of land surface temperatures derived from AATSR and MODIS data. Remote Sens Environ 97:288–300CrossRefGoogle Scholar
  5. Elvidge CD (1988) Thermal infrared reflectance of dry plant materials: 2.5–20.0 µm. Remote Sens Environ 26:265–285CrossRefGoogle Scholar
  6. French AN, Schmugge, TJ, Kustas WP (2000) Discrimination of senescent vegetation using thermal emissivity contrast. Remote Sens Environ 74:2), 249–254CrossRefGoogle Scholar
  7. Li Z-L, Becker F (1993) Feasibility of land surface temperature and emissivity determination from AVHRR data. Remote Sens Environ 43:67–85CrossRefGoogle Scholar
  8. Mannstein H (1987) Surface energy budget, surface temperature and thermal inertia. In: Vaughan RA, Reidel D (eds) Remote sensing applications in meteorology and climatology, Reidel, 1987, NATO ASI Ser. C: Math. Phys. Sci., vol. 201. Dordrecht, The Netherlands, pp 391–410Google Scholar
  9. Masuoka E, Fleig A, Wolfe RE, Patt F (1998) Key characteristics of MODIS data products. IEEE Trans Geosci Remote Sens 36:1313–1323ADSCrossRefGoogle Scholar
  10. Salisbury JW, D’Aria DM (1992) Emissivity of terrestrial materials in the 8–14 µm atmospheric window. Remote Sens Environ 42:83–106ADSCrossRefGoogle Scholar
  11. Sellers PJ, Hall FG, Asrar G, Strebel, DE, Murphy RE (1988) The first ISLSCP field experiment (FIFE). Bull Am Meteorol Soc 69(1):22–27CrossRefGoogle Scholar
  12. Snyder WC, Wan Z, Zhang Y, Feng Y-Z (1998) Classification-based emissivity for land surface temperature measurement from space. Int J Remote Sens 19:2753–2574CrossRefGoogle Scholar
  13. Wan Z (2008) New refinements and validation of the MODIS land-surface temperature/emissivity products. Remote Sens Environ 112:59–74CrossRefGoogle Scholar
  14. Wan Z, Dozier J (1996) A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Trans Geosci Remote Sens 34:892–905ADSCrossRefGoogle Scholar
  15. Wan Z, Li Z-L (1997) A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data. IEEE Trans Geosci Remote Sens 35:980–996ADSCrossRefGoogle Scholar
  16. Wan Z, Wang P, Li X (2004a) Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in the Great Plains, USA. Int J Remote Sens 25:61–72CrossRefGoogle Scholar
  17. Wan Z, Zhang Y, Li Z-L, Wang R, Salomonson VV, Yves A, Bosseno R, Hanocq JF (2002a) Preliminary estimate of calibration of the Moderate Resolution Imaging Spectroradiometer thermal infrared data using Lake Titicaca. Remote Sens Environ 80:497–515CrossRefGoogle Scholar
  18. Wan Z, Zhang Y, Zhang YQ, Li Z-L (2002b) Validation of the land-surface temperature products retrieved from Moderate Resolution Imaging Spectroradiometer data. Remote Sens Environ 83:163–180CrossRefGoogle Scholar
  19. Wan Z, Zhang Y, Zhang YQ, Li Z-L (2004b) Quality assessment and validation of the global land surface temperature. Int J Remote Sens 25:261–274CrossRefGoogle Scholar
  20. Wang K, Wan Z, Wang P, Sparrow M, Liu J, Zhou X, Haginoya S (2005) Estimation of surface long wave radiation and broadband emissivity using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature/emissivity products. J Geophys Res 110:D11109, doi:10.1029/2004JD005566ADSCrossRefGoogle Scholar
  21. Wang K, Li Z, Cribb M (2006) Estimation of evaporative fraction from a combination of day and night land surface temperatures and NDVI: a new method to determine the Priestley-Taylor parameter. Remote Sens Environ 102:293–305CrossRefGoogle Scholar
  22. Wolfe RE, Nishihama M, Fleig AJ, Kuyper JA, Roy DP, Storey JC, Patt FS (2002) Achieving sub-pixel geolocation accuracy in support of MODIS land science. Remote Sens Environ 83:31–49CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.ICESSUniversity of CaliforniaSanta BarbaraUSA

Personalised recommendations