Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin

Journal article (2017)

Authors

Nana Li Chinese Academy of Sciences, Tsinghua University, Joint Center for Global Change Studies
Li Jia Joint Center for Global Change Studies, Chinese Academy of Sciences
Jing Lu Joint Center for Global Change Studies, Chinese Academy of Sciences
M. Menenti Chinese Academy of Sciences, Optical and Laser Remote Sensing - CEG
J. Zhou Optical and Laser Remote Sensing - CEG
Research Group
Optical and Laser Remote Sensing (CEG) (TU Delft)
Copyright: © 2017 Nana Li, Li Jia, Jing Lu, M. Menenti, J. Zhou
DOI: https://doi.org/10.1117/1.JRS.11.016028
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Published Date

01-01-2017

Language

English

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Faculty

Civil Engineering & Geosciences

Department

Geoscience and Remote Sensing

Research Group

Optical and Laser Remote Sensing

Abstract

The regional surface soil heat flux (G0) estimation is very important for the large-scale land surface process modeling. However, most of the regional G0 estimation methods are based on the empirical relationship between G0 and the net radiation flux. A physical model based on harmonic analysis was improved (referred to as "HM model") and applied over the Heihe River Basin northwest China with multiple remote sensing data, e.g., FY-2C, AMSR-E, and MODIS, and soil map data. The sensitivity analysis of the model was studied as well. The results show that the improved model describes the variation of G0 well. Land surface temperature (LST) and thermal inertia (Γ) are the two key input variables to the HM model. Compared with in situ G0, there are some differences, mainly due to the differences between remote-sensed LST and the in situ LST. The sensitivity analysis shows that the errors from-7 to-0.5K in LST amplitude and from-300 to 300J m-2 K-1 s-0.5 in Γ will cause about 20% errors, which are acceptable for G0 estimation.

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