Surface Temperature

Other Names:

Thermal infrared imagery


Remote sensing of temperature uses the amount of radiation reflected or emitted in the thermal infrared portion of the electromagnetic spectrum. The thermal infrared range of the EMS is generally considered to be between 3 and 14 µm. Due to absorbtion by atmospheric water in some portions of the EMS, wavelengths for measuring thermal infrared radiation are generally considered to be from 3-5 µm and 8-14 µm. A number of factors affect the amount of thermal infrared radiation reflected or emitted from the land surface. These include:

  • variations in sun angle
  • composition, density, and texture of the components of the land
  • topography
  • moisture at the surface
  • climate
  • vegetation canopy characteristics
  • recent temperature history

Remotely-sensed surface temperature data are commonly used in studies of water temperature or ocean current flows. Surface temperature, however, also has applications to terrestrial land management, and has been used in conjunction with spectral vegetation indices to assess rangeland cover and change. Surface temperature data are also a key input into the biophysical models used to estimate attributes like evapotranspiration or net primary productivity.

Similar Methods

Thermal anomalies representing events like active fires are created from thermal infrared or surface temperature images.


Output is an image layer/dataset with values representing either emissivity of thermal infrared radiation or surface temperature.

Successful Rangeland Uses

  • For Allen et al. (2005), surface temperature measurements from the Landsat TM sensors is a key input to the METRIC model for estimating evapotranspiration.
  • Lambin and Erlich (1997) used changes in surface temperature measurements and vegetation indices to detect land-cover changes at a continental scale in Africa. They looked for deviations from a normal seasonal trajectory of temperature and greenness to detect land cover changes from AVHRR imagery.
  • Moran et al. (1994). defined a measure of plant stress, the water deficit index, using a combination of surface temperature and spectral data.
  • The standard surface temperature product from the MODIS sensor is used to detect “thermal anomalies” (i.e., active fires). The thermal anomaly layer is a standard MODIS product used by a number of land management agencies

Application References

  • Allen, R.G., Tasumi, M., Morse, A., and R. Trezza. 2005. A Landsat-based energy balance and evapotranspiration model in Western US water rights regulation and planning. Irrigation and Drainage Systems 19:251-268.
  • Lambin, E.F., and D. Erlich. 1997. Land-cover changes in Sub-Saharan Africa (1982-1991): application of a change index based on remotely sensed surface temperature and vegetation indices at a continental scale. Remote Sensing of the Environment 61(2):181-200.
  • Moran, M.S., Clarke, T.R., Inoue, Y., and A. Vidal. 1994. Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Remote Sensing of the Environment 46:246-263.

Technical References

  • Lillesand, T. M., and R. W. Kiefer 1994. Remote sensing and image interpretation. John Wiley & Sons, Inc., New York.
  • Lugassia, R., Ben-Dorb, E. and G. Echelc. 2009. A spectral-based method for reconstructing spatial distributions of soil surface temperature during simulated fire events. Remote Sensing of the Environment 114:322-331.


In most cases, surface temperature will be an input to another remote sensing product that produces information more directly related to rangeland management. One limitation to remotely-sensed surface temperature measurements is that the values recorded by the sensor are a combination of soil surface and vegetation temperature. This is problematic when used as inputs to biophysical models because most models need temperature of the vegetation only.

Data Inputs

Surface temperature is calculated from the thermal infrared radiance values recorded by a sensor. These readings are calibrated to surface temperature.

Software/Hardware Requirements

For the most part, existing or standard-product surface temperature datasets are used rather than calculating new surface temperature datasets manually from raw imagery.

Sample Graphic

N.M. Short’s Remote Sensing Tutorial

Additional Information

  • The NASA Jet Propulsion Lab (JPL) produced a video describing thermal remote sensing called “Infrared: more than your eyes can see.” The video can be found at: Requires RealPlayer.

Existing datasets

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