Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe
Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe
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DOI：
10.1016/j.rse.2011.08.003
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发表时间：
2011-12-15
影响因子：
13.5
通讯作者：
Bittelli, M.
中科院分区：
文献类型：
--
作者：
Brocca, L.;Hasenauer, S.;Bittelli, M.
从各种遥感传感器获取的全球土壤湿度产品正变得越来越容易获得，具有几乎每天的时间分辨率。主动和被动微波传感器通常被认为是从太空中获取土壤水分的最佳技术。Aqua卫星上的地球观测系统先进微波扫描辐射计（AMSR-E）和MetOp（气象业务）卫星上的先进散射计（ASCAT）是近年来最广泛用于土壤湿度反演的传感器。然而，由于空间分辨率、观测深度和测量不确定性的差异，用现场观测和/或模拟数据验证卫星数据并不简单。在这项研究中，通过使用位于欧洲4个国家（意大利、西班牙、法国和卢森堡）的17个站点的观测和模拟土壤湿度数据，对ASCAT和AMSR-E传感器估算土壤湿度的可靠性进行了全面评估。对于卫星数据，考虑了采用AMSR-E数据实现三种不同算法生成的产品：(i)土地参数检索模型（LPRM）， （ii）标准NASA（美国国家航空航天局）算法，（iii）极化比指数（PRI）。对于维也纳理工大学ASCAT， TUWIEN，采用变化检测算法。采用指数滤波法对根区土壤水分进行了分析。采用线性回归校正和累积密度函数（CDF）匹配两种不同的标度策略，消除了卫星土壤湿度数据与站点土壤湿度数据之间的系统差异。结果显示为相对土壤湿度值（即介于0和1之间）和气候期望的异常。在基于AMSR-E传感器数据的3种土壤湿度产品中，大多数站点使用LPRM算法与观测数据和模型数据的相关性最高。考虑到类似5厘米土层的相对土壤湿度值，TUWIEN ASCAT产品在法国和意大利中部的所有站点上都优于AMSR-E，而在所有其他地区也获得了类似的结果。具体而言，ASCAT和AMSR-E-LPRM与观测（建模）数据的平均相关系数分别为0.71（0.74）和0.62（0.72）。当采用指数滤波和CDF匹配方法时，两卫星产品的相关值分别增加到0.81（0.81）和0.69（0.77）。另一方面，考虑到异常，相关性值降低，但更重要的是，在这种情况下，ASCAT在除西班牙网站外的所有网站上都优于所有其他产品。总体而言，各卫星土壤水分产品的可靠性随着植被密度的增加而降低，与前人的研究结果一致。结果概述了ASCAT和AMSR-E在欧洲不同地区的可靠性和稳健性，从而突出了这些数据集在洪水预报和数值天气预报等业务应用中有效使用的优点和缺点。(C) 2011爱思唯尔公司版权所有。
Global soil moisture products retrieved from various remote sensing sensors are becoming readily available with a nearly daily temporal resolution. Active and passive microwave sensors are generally considered as the best technologies for retrieving soil moisture from space. The Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) on-board the Aqua satellite and the Advanced SCATterometer (ASCAT) on-board the MetOp (Meteorological Operational) satellite are among the sensors most widely used for soil moisture retrieval in the last years. However, due to differences in the spatial resolution, observation depths and measurement uncertainties, validation of satellite data with in situ observations and/or modelled data is not straightforward. In this study, a comprehensive assessment of the reliability of soil moisture estimations from the ASCAT and AMSR-E sensors is carried out by using observed and modelled soil moisture data over 17 sites located in 4 countries across Europe (Italy, Spain, France and Luxembourg). As regards satellite data, products generated by implementing three different algorithms with AMSR-E data are considered: (i) the Land Parameter Retrieval Model, LPRM, (ii) the standard NASA (National Aeronautics and Space Administration) algorithm, and (iii) the Polarization Ratio Index, PRI. For ASCAT the Vienna University of Technology, TUWIEN, change detection algorithm is employed. An exponential filter is applied to approach root-zone soil moisture. Moreover, two different scaling strategies, based respectively on linear regression correction and Cumulative Density Function (CDF) matching, are employed to remove systematic differences between satellite and site-specific soil moisture data. Results are shown in terms of both relative soil moisture values (i.e., between 0 and 1) and anomalies from the climatological expectation.Among the three soil moisture products derived from AMSR-E sensor data, for most sites the highest correlation with observed and modelled data is found using the LPRM algorithm. Considering relative soil moisture values for an similar to 5 cm soil layer, the TUWIEN ASCAT product outperforms AMSR-E over all sites in France and central Italy while similar results are obtained in all other regions. Specifically, the average correlation coefficient with observed (modelled) data equals to 0.71 (0.74) and 0.62 (0.72) for ASCAT and AMSR-E-LPRM, respectively. Correlation values increase up to 0.81 (0.81) and 0.69 (0.77) for the two satellite products when exponential filtering and CDF matching approaches are applied. On the other hand, considering the anomalies, correlation values decrease but, more significantly, in this case ASCAT outperforms all the other products for all sites except the Spanish ones. Overall, the reliability of all the satellite soil moisture products was found to decrease with increasing vegetation density and to be in good accordance with previous studies. The results provide an overview of the ASCAT and AMSR-E reliability and robustness over different regions in Europe, thereby highlighting advantages and shortcomings for the effective use of these data sets for operational applications such as flood forecasting and numerical weather prediction. (C) 2011 Elsevier Inc. All rights reserved.