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The estimation of distribution in field scale of surface aerodynamic roughness using remote sensing data

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4 Author(s)
Ren-Hua Zhang ; Inst. of Geogr. Sci. & Natural Resources Res., Chinese Acad. of Sci., Beijing ; Cai-Ying Zhu ; Xiao-Min Sun ; Zhi-Llin Zhu

This paper presents a new way to calculate the aerodynamic roughness using the surface geometric roughness retrieved from SAR (Synthetic Aperture Radar) and TM thermal infrared image data. On the one hand, the SPM (Small Perturbation Model) was used as a theoretical SAR backscattering model to describe the relationship between the SAR backscattering coefficient and the surface geometric roughness and its dielectric constant retrieved from the physical model between the soil thermal inertia and the soil moisture with the simultaneous TM thermal infrared image data and the ground microclimate data. On the basis of the SAR image matching with the TM image, the non-volume scattering surface geometric information was obtained from the SPM model at the TM image pixel scale, and the ground pixel surface's equivalent geometric roughness - height standard RMS (Root Mean Square) was achieved from the geometric information by the transformation of the typical topographic factors. The vegetation (wheat, tree) height retrieved from spectrum model was also transferred into its equivalent geometric roughness. A complete two-dimensional distribution map of the equivalent geometric roughness over the experimental area was produced by the data mosaic technique. On the other hand, according to the atmosphere eddy currents theory, the aerodynamic surface roughness was iterated out with the atmosphere stability correction method using the wind and the temperature profiles data measured at several typical fields such as bare soil field and vegetation field. After having analyzed the effect of surface equivalent geometric roughness together with dynamic and thermodynamic factors on the aerodynamic surface roughness within the working area. The final result retrieved from above series of models was validated by the in-situ measured data

Published in:

Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International  (Volume:7 )

Date of Conference:

20-24 Sept. 2004

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