TY - JOUR
T1 - Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin
AU - Li, Nana
AU - Jia, Li
AU - Lu, Jing
AU - Menenti, Massimo
AU - Zhou, J.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - 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.
AB - 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.
KW - arid and semiarid area
KW - Harmonic analysis model
KW - regional soil heat flux
KW - remote sensing data
KW - thermal inertia
UR - http://www.scopus.com/inward/record.url?scp=85013500030&partnerID=8YFLogxK
UR - http://resolver.tudelft.nl/uuid:1cbd8845-dd4c-40a7-b893-72c4e0a6f21f
U2 - 10.1117/1.JRS.11.016028
DO - 10.1117/1.JRS.11.016028
M3 - Article
AN - SCOPUS:85013500030
SN - 1931-3195
VL - 11
JO - Journal of Applied Remote Sensing
JF - Journal of Applied Remote Sensing
IS - 1
M1 - 016028
ER -