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首页> 外文期刊>Geophysical Research Letters >Improved prediction of quasi-global vegetation conditions using remotely-sensed surface soil moisture
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Improved prediction of quasi-global vegetation conditions using remotely-sensed surface soil moisture

机译:利用遥感表层土壤水分改进准全球植被状况的预测

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摘要

The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS(AMSR-E)into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.
机译:通过计算遥感植被指数(VI)与同化后获得的表层土壤水分反演前后获得的土壤湿度估算值之间的滞后秩相关性,评估用于农业干旱监测的卫星表面土壤水分反演的增加值。将高级微波扫描辐射仪EOS(AMSR-E)转换为土壤水平衡模型。较高的土壤水分/ VI滞后相关性意味着使用当前土壤水分的估计值来预测未来植被状况的能力增强。结果表明,对AMSR-E表层土壤水分的吸收同化作用显着改善了全球干旱监测系统的性能,特别是在世界上缺乏高质量降雨观测值的人烟稀少的地区。

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