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

机译:利用遥感数据估算地表空气动力学粗糙度场尺度分布

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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
机译:本文提出了一种使用从SAR(合成孔径雷达)和TM热红外图像数据获取的表面几何粗糙度来计算空气动力学粗糙度的新方法。一方面,将SPM(小扰动模型)用作理论SAR背散射模型,以描述SAR背散射系数与表面几何粗糙度之间的关系,以及从土壤热惯性与物理惯性之间的物理模型中获得的介电常数。利用TM热红外图像数据和地面微气候数据同时获得土壤水分。在SAR图像与TM图像匹配的基础上,从TM图像像素尺度的SPM模型获得了非体积散射表面的几何信息,并获得了地面像素表面的等效几何粗糙度-高度标准RMS(均方根) )是通过转换典型地形因子从几何信息中获得的。从光谱模型中检索到的植被(小麦,树木)高度也被转换为等效的几何粗糙度。通过数据镶嵌技术生成了整个实验区域上等效几何粗糙度的完整二维分布图。另一方面,根据大气涡流理论,利用大气稳定性校正方法,利用在裸土场和植被场等几个典型场上测得的风和温度剖面数据,用迭代法求出了空气动力学表面粗糙度。在分析了表面等效几何粗糙度以及动态和热力学因素对工作区域内空气动力学表面粗糙度的影响之后。从上述一系列模型中获得的最终结果已通过现场测量数据进行了验证

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