Science in China Series D: Earth Sciences

, Volume 46, Issue 4, pp 342–355 | Cite as

A remote sensing model for monitoring soil evaporation based on differential thermal inertia and its validation

  • Renhua Zhang
  • Xiaomin Sun
  • Zhilin Zhu
  • Hongbo Su
  • Xinzhai Tang


The presently applied remote sensing algorithms and approaches to monitor soil surface fluxes are reviewed at the beginning of this paper, and the bottleneck of the estimation of soil surface fluxes lies in the dependence on non remotely sensed parameters (NRSP). A soil surface evaporation model based on differential thermal inertia, only using remotely sensed information, has thus been proposed after many experiments. The key of the model is to derive soil moisture availability by differential thermal inertia rather than local soil parameters such as soil properties and type. Bowen ratio is estimated by means of soil moisture availability instead of NRSP, such as temperature and wind velocity. Net radiation flux and apparent thermal inertia have been used for soil heat flux parameterization, therefore, the objective of evaporation (latent heat flux) inversion for bare soil only by remotely sensed information can be realized. Two NOAA-AVHRR five-band images, taken at Shapotou northwest of China when soil surface temperature approximated to the highest and lowest of the region, were applied in combination with the ground surface information measured synchronously. The distribution of soil evaporation in Shapotou could be determined. Model verification has been performed between the measured soil surface evaporation and the corresponding calculated value of the images, and the result has proved model to be feasible. Finally, the possible errors and further modifications when applying model to fulling vegetation canopy have been discussed.


differential thermal inertia relative residual thermal inertia (RSTI) Bowen ratio soil surface evaporation 


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Copyright information

© Science in China Press 2003

Authors and Affiliations

  • Renhua Zhang
    • 1
  • Xiaomin Sun
    • 1
  • Zhilin Zhu
    • 1
  • Hongbo Su
    • 1
  • Xinzhai Tang
    • 1
  1. 1.Institute of Geographical Science and Natural ResourcesChinese Academy of SciencesBeijingChina

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