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Journal of Applied Remote Sensing

Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin
Author(s): Nana Li; Li Jia; Jing Lu; Massimo Menenti; Jie Zhou
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Paper 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

Paper Details

Date Published: 17 February 2017
PDF: 18 pages
J. Appl. Rem. Sens. 11(1) 016028 doi: 10.1117/1.JRS.11.016028
Published in: Journal of Applied Remote Sensing Volume 11, Issue 1
Show Author Affiliations
Nana Li, Institute of Remote Sensing and Digital Earth (China)
Tsinghua Univ. (China)
Joint Ctr. for Global Change Studies (China)
Li Jia, Institute of Remote Sensing and Digital Earth (China)
Joint Ctr. for Global Change Studies (China)
Jing Lu, Institute of Remote Sensing and Digital Earth (China)
Joint Ctr. for Global Change Studies (China)
Massimo Menenti, Institute of Remote Sensing and Digital Earth (China)
Technische Univ. Delft (Netherlands)
Jie Zhou, Institute of Remote Sensing and Digital Earth (China)


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