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Retrieving soil moisture for non-forested areas using PALS radiometer measurements in SMAPVEX12 field campaign

机译:在SMAPVEX12野外活动中使用PALS辐射计测量来获取非林区的土壤水分

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In this paper, soil moisture retrievals of surface soil moisture was investigated using L-band brightness temperature under diverse conditions and land cover types. The study focused on the PALS (Passive Active L-band System) radiometer data collected during the SMAPVEXI2 (Soil Moisture Active Passive Validation Experiment 2012) field experiment which took place in southern Manitoba, Canada in 2012. The experiment domain covers croplands with high clay content as well as croplands and grasslands with sandy soils. A retrieval algorithm was parameterized for these specific land types. The formulation of the retrieval algorithm is based on a traditional surface scattering assumption. Based on this data set we found that for the clayey croplands the surface scattering assumption is inadequate, and that the algorithm needed significant tuning for the sandy soils. Empirically-based parameters for retrieving soil moisture under these conditions were developed. We also applied the parameterized algorithm to the retrieval of soil moisture for the entire experiment domain. We found that the use of sub grid modeling improves the retrieval performance to a satisfactory level despite the challenging land types encountered. (C) 2016 Elsevier Inc. All rights reserved.
机译:本文在不同条件和土地覆盖类型下,利用L波段亮度温度研究了表层土壤水分的土壤水分反演。这项研究的重点是2012年在加拿大马尼托巴省南部进行的SMAPVEXI2(2012年土壤水分主动被动验证实验)野外试验期间收集的PALS(被动主动L波段系统)辐射计数据。含量以及有沙土的农田和草原。针对这些特定土地类型的检索算法已参数化。检索算法的制定是基于传统的表面散射假设。根据此数据集,我们发现对于粘土质农田,表面散射假设是不充分的,并且该算法需要对沙土进行显着调整。开发了在这些条件下用于获取土壤水分的基于经验的参数。我们还将参数化算法应用于整个实验范围内的土壤水分检索。我们发现,尽管遇到了具有挑战性的土地类型,但使用子网格模型仍将检索性能提高到令人满意的水平。 (C)2016 Elsevier Inc.保留所有权利。

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