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Soil Moisture and Vegetation Water Content Retrieval Using QuikSCAT Data

机译:利用QuikSCAT数据反演土壤水分和植被含水量

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Climate change and hydrological cycles can critically impact future water resources. Uncertainties in current climate models result in disagreement on the amount of water resources. Soil moisture and vegetation water content are key environmental variables on evaporation and transpiration at the land–atmosphere boundary. Radar remote sensing helps to improve our estimate of water resources spatially and temporally. This work proposes a backscattered power formulation for the Ku-band. Li et al. (2010) retrieved soil moisture and vegetation water content values using Windsat data and simultaneous collocated QuikSCAT backscattered power are used to estimate different parameters of backscatter formulation. These parameters are used to estimate soil moisture and vegetation water content using QuikSCAT power everywhere and every day during the summer season. The 2-folded cross validation method is used to evaluate the performance of soil moisture and vegetation water content retrieval. A relatively large correlation is observed between vegetation water content using WindSat and QuikSCAT data in land classes of Evergreen Needleleaf, Evergreen Broadleaf, Deciduous Broadleaf, and Mixed Forests. Similarly, the retrieved soil moisture using QuikSCAT in areas with bare surface fraction of greater than 60% shows relatively high correlation with WindSat values. QuikSCAT satellite collects data over land globally almost every day. Therefore, QuikSCAT data can be used to generate a global map of soil moisture and vegetation water content daily from 2000 to 2009.
机译:气候变化和水文循环会严重影响未来的水资源。当前气候模型的不确定性导致水资源量上的分歧。土壤水分和植被含水量是影响陆地-大气边界蒸发和蒸腾作用的关键环境变量。雷达遥感有助于改善我们在空间和时间上对水资源的估计。这项工作提出了Ku波段的反向散射功率公式。 Li等。 (2010年)使用Windsat数据获取的土壤水分和植被含水量值以及同时并置的QuikSCAT背向散射功率用于估算背向散射配方的不同参数。这些参数用于在夏季的任何地方和每天使用QuikSCAT电源估算土壤湿度和植被含水量。 2折交叉验证方法用于评估土壤水分和植被含水量检索的性能。在常绿针叶,常绿阔叶,落叶阔叶和混交林的土地类别中,使用WindSat和QuikSCAT数据观察到的植被含水量之间具有相对较大的相关性。同样,使用QuikSCAT在裸露表面分数大于60%的区域中获取的土壤水分与WindSat值具有相对较高的相关性。 QuikSCAT卫星几乎每天都在全球范围内收集数据。因此,QuikSCAT数据可用于生成2000年至2009年每天的土壤水分和植被含水量全球地图。

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