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Evaluation of NASA SMAP soil moisture data in wet and dry spellsusing in situ observations

机译:湿法湿法湿法湿法评价原位观察的评价

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Ground-based measurements of soil moisture (SM) present accurate time series of this variable whereas the spatial disparity ofSM is unknown. This knowledge gap can be filled using remote sensed datasets that provide high spatial resolution informationof SM. This study evaluates remote sensed data from the NASA Soil Moisture Active Passive (SMAP) satellite. The data from SMAPwere compared with the in situ observations collected by the International Soil Moisture Network. The evaluation results of remote sensed SM products were assessed in diverse climate divisions as well as different main land cover classes in the state of Kansas in both wet and dry spells through correlation analysis. The spatial analysis revealed the prominent impact of climate divisions and vegetation types on data. The results indicated that SMAP L4 SM retrievals are generally better when considering the impact of both climate and land cover in analyzing the data. Using both climate divisions and vegetation types suggest a more robust understanding of relationship between data sources specially in short dry and wet spells, which may play critical role for agriculture.
机译:土壤湿度(SM)的基于地基测量本变量的准确时间序列,而SSM的空间视差未知。可以使用提供SM提供高空间分辨率信息的远程感测数据集来填充此知识间隙。本研究评估了来自美国宇航局土壤湿气活性无源(SMAP)卫星的遥感数据。与国际土壤湿度网络收集的原位观察相比,Smapwere的数据。通过相关性分析,在多样化的气候划分中评估了遥感SM产物的评估结果,以及堪萨斯州湿法和干性的不同主要土地覆盖课程。空间分析揭示了气候划分和植被类型对数据的突出影响。结果表明,在考虑气候和陆地覆盖在分析数据时,SMAP L4 SM检索通常更好。使用气候部门和植被类型建议更加强大地了解数据来源之间的关系,特别是短干和湿法的法术,这可能对农业发挥着关键作用。

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