Soil Moisture Estimation Under Low Vegetation Cover Using a Multi-Angular Polarimetric Decomposition
Soil Moisture Estimation Under Low Vegetation Cover Using a Multi-Angular Polarimetric Decomposition
复制标题
DOI：
10.1109/tgrs.2012.2209433
复制
发表时间：
2013-04
影响因子：
8.2
通讯作者：
T. Jagdhuber;I. Hajnsek;A. Bronstert;K. Papathanassiou
中科院分区：
文献类型：
--
作者：
T. Jagdhuber;I. Hajnsek;A. Bronstert;K. Papathanassiou
研究了利用L波段全极化合成孔径雷达数据，利用多角度极化分解估计低层农业植被下土壤体积水分的方法。雷达偏振测量提供了一个框架，将后向散射信号分解成不同的典型散射机制，涉及到来自下层土壤和植被覆盖的散射贡献。多角度观测的多样性进一步增加了土壤水分反演的信息空间，从而实现了更高的反演速度和稳定的反演性能。作为2008年不透明运动的一部分，所开发的方法被应用于德国航空航天中心的ESAR传感器获取的多角度L波段数据集。获得的结果与OPAKE团队在各种植被覆盖的农田上收集的地面测量结果进行了比较。对估计的土壤湿度与地面测量的土壤湿度进行验证，结果表明，包括各种作物类型的所有试验田在内，均方根误差水平为6-8%。
The estimation of volumetric soil moisture under low agricultural vegetation from fully polarimetric synthetic aperture radar (SAR) data at L-band using a multi-angular polarimetric decomposition is investigated. Radar polarimetry provides the framework to decompose the backscattered signal into different canonical scattering mechanisms referring to scattering contributions from the underlying soil and the vegetation cover. Multi-angular observation diversity further increases the information space for soil moisture inversion enabling higher inversion rates and a stable inversion performance. The developed approach was applied on the multi-angular L-band data set acquired by German Aerospace Center's ESAR sensor as part of the OPAQUE campaign in 2008. The obtained results are compared against ground measurements collected by the OPAQUE team over a variety of vegetated agricultural fields. The validation of the estimated against ground measured soil moisture results in an root mean square error level of 6-8 vol.% including all test fields with a variety of crop types.