17 February 2017 Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin
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Abstract
The regional surface soil heat flux ( G 0 ) estimation is very important for the large-scale land surface process modeling. However, most of the regional G 0 estimation methods are based on the empirical relationship between G 0 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 G 0 well. Land surface temperature (LST) and thermal inertia ( Γ ) are the two key input variables to the HM model. Compared with in situ G 0 , 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 0.5    K in LST amplitude and from 300 to 300    J m 2 K 1
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Nana Li, Nana Li, Li Jia, Li Jia, Jing Lu, Jing Lu, Massimo Menenti, Massimo Menenti, Jie Zhou, Jie Zhou, } "Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin," Journal of Applied Remote Sensing 11(1), 016028 (17 February 2017). https://doi.org/10.1117/1.JRS.11.016028 . Submission: Received: 20 April 2016; Accepted: 10 January 2017
Received: 20 April 2016; Accepted: 10 January 2017; Published: 17 February 2017
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