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Sensitivity of microwave remotely-sensed soil moisture to soil properties

机译:微波远程感应土壤水分对土壤性质的敏感性

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Surface soil moisture is important in a number of disciplines including agricultural scheduling, water resource management, and weather forecasting. While conventional methods of surface soil moisture determination are labor intensive and oflimited spatial scale, ground- and aircraft-based microwave remote sensing systems provide repetitive measurements over large areas. However, it is unclear how the remotely-sensed soil moisture reflects the variations in soil parameters used as inputvariables in soil moisture retrieval algorithms. Data from a multi-frequency passive microwave remote sensing experiment were used to study the sensitivity of an algorithm to soil texture, bulk density and surface roughness. The algorithm was relativelyinsensitive to texture, slightly sensitive to bulk density and highly sensitive to surface roughness (RMS). For the most part, the deviations in volumetric soil moisture from the baseline were more pronounced under wet conditions than under dryconditions, and these deviations were also independent of wavelength. This study implies that areal average values of texture variables and bulk density can serve as convenient inputs into soil moisture algorithms.
机译:表面土壤水分在许多学科中是重要的,包括农业调度,水资源管理和天气预报。虽然常规的表面土壤湿度测定方法是劳动密集型和空间秤,但基于地面和飞机的微波遥感系统提供了大面积的重复测量。然而,目前还不清楚远程感测的土壤水分如何反映在土壤湿度检索算法中用作InputVariables的土壤参数的变化。来自多频无源微波遥感实验的数据用于研究算法对土壤纹理,散装密度和表面粗糙度的敏感性。该算法对纹理相比,对堆积密度略微敏感,对表面粗糙度高度敏感(RMS)。在大多数情况下,在基线中的体积土壤水分在潮湿条件下比在干湿条件下更明显,这些偏差也与波长无关。本研究意味着质地变量和散装密度的面值平均值可以作为土壤湿度算法的方便输入。

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