首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >ANALYZING THE IMPACT OF USING THE SRP (SIMPLIFIED ROUGHNESS PARAMETERIZATION) METHOD ON SOIL MOISTURE RETRIEVAL OVER DIFFERENT REGIONS OF THE GLOBE
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ANALYZING THE IMPACT OF USING THE SRP (SIMPLIFIED ROUGHNESS PARAMETERIZATION) METHOD ON SOIL MOISTURE RETRIEVAL OVER DIFFERENT REGIONS OF THE GLOBE

机译:用SRP(简化粗糙度参数化)法对地球不同地区土壤水分检索的影响分析

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This paper focuses on a new approach to account for soil roughness effects in the retrieval of soil moisture (SM) at L-band in the framework of the SMOS (Soil Moisture and Ocean Salinity) mission: the Simplified Roughness Parameterization (SRP). While the classical retrieval approach considers SM and τ_(NAD) (vegetation optical depth) as retrieved parameters, this approach is based on the retrieval of SM and the TR parameter combining τ_(NAD) and soil roughness (TR = τ_(NAD) + H_R/2). Different roughness parameterizations were tested to find the best correlation (R), bias and unbiased RMSE (ubRMSE) when comparing homogeneous retrievals of SM and in situ SM measurements carried out at the VAS (Valencia Anchor Station) vineyard field. The highest R (0.68) and lowest ubRMSE (0.056 m~3 m~(-3)) were found using the SRP method. Using the SMOS observations comparisons against several SM networks were also made: AACES, SCAN, watersheds and SMOSMANIA. SM was retrieved over all these stations. The SRP and another similar approach (SRP2) improved the averaged ubRMSE, while the SRP2 method leaded to higher correlation values (R). A global underestimation of SM was noticed, which may be linked to the differences in the sampling depths of the L-band observations (~ 0-3cm for both Elbara-II and SMOS) and of the in situ measurements (~ 0-5 cm).
机译:本文重点介绍了在SMOS(土壤水分和海洋盐度)任务框架中的土壤湿度(SM)中的土壤粗糙度效应的新方法:简化粗糙度参数化(SRP)。虽然经典的检索方法考虑SM和τ_(NAD)(植被光学深度)作为检索的参数,这种方法是基于SM的检索和TR参数组合τ_(NAD)和土壤粗糙度(TR =τ_(NAD)+ H_R / 2)。在比较SM的同质检索和在VAS(瓦伦西亚锚站)葡萄园领域进行的同质检索时,测试了不同的粗糙度参数化以查找最佳相关性(R),偏置和非偏见的RMSE(UBRMSE)。使用SRP方法发现最高的R(0.68)和最低ubrmse(0.056m〜3 m〜(3))。使用SMOS观测,还进行了针对几个SM网络的比较:A次数,扫描,流域和SMOSMANIA。在所有这些站上检索SM。 SRP和另一种类似的方法(SRP2)改善了平均ubrmse,而SRP2方法引入了更高的相关值(R)。注意到SM的全球低估,这可能与L波段观察的采样深度的差异相关联(Elbara-II和SMOS的〜0-3cm)和原位测量(〜0-5cm) )。

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