Print Email Facebook Twitter Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin Title Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin Author Li, Nana (Chinese Academy of Sciences; Tsinghua University; Joint Center for Global Change Studies) Jia, Li (Chinese Academy of Sciences; Joint Center for Global Change Studies) Lu, Jing (Chinese Academy of Sciences; Joint Center for Global Change Studies) Menenti, M. (TU Delft Optical and Laser Remote Sensing; Chinese Academy of Sciences) Zhou, J. (TU Delft Optical and Laser Remote Sensing) Date 2017-01-01 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. Subject arid and semiarid areaHarmonic analysis modelregional soil heat fluxremote sensing datathermal inertia To reference this document use: http://resolver.tudelft.nl/uuid:1cbd8845-dd4c-40a7-b893-72c4e0a6f21f DOI https://doi.org/10.1117/1.JRS.11.016028 Source Journal of Applied Remote Sensing, 11 (1) Part of collection Institutional Repository Document type journal article Rights © 2017 Nana Li, Li Jia, Jing Lu, M. Menenti, J. Zhou Files PDF JARS_11_1_016028.pdf 5.19 MB Close viewer /islandora/object/uuid:1cbd8845-dd4c-40a7-b893-72c4e0a6f21f/datastream/OBJ/view