Further validation of a new methodology for surface moisture and vegetation optical depth retrieval
Further validation of a new methodology for surface moisture and vegetation optical depth retrieval
复制标题
DOI：
10.1080/0143116031000095934
复制
发表时间：
2003-01
影响因子：
3.4
通讯作者：
R. de Jeu;M. Owe
中科院分区：
文献类型：
--
作者：
R. de Jeu;M. Owe
提出了对最近开发的土壤湿度和光学深度反演算法的一系列验证研究。该方法主要是理论性的，并使用非线性迭代优化程序来求解双偏振卫星微波亮度温度的两个参数的简单辐射传递方程。卫星反演数据源自夜间 6.6 GHz Nimbus 扫描多通道微波辐射计 (SMMR) 观测结果，并与来自美国、蒙古、土库曼斯坦和俄罗斯的土壤湿度数据集进行了比较。表面温度也是模型中的未知参数，是从 37 GHz 垂直偏振亮度温度离线得出的。新的理论方法独立于土壤湿度的现场观察或冠层生物物理测量，并且可以在微波区域的任何波长下使用。土壤湿度反演与不同地点的表面湿度观测结果进行了很好的比较。植被光学深度也与归一化植被指数（NDVI）的时间序列进行了很好的比较，并显示出相似的季节模式。从全球角度来看，卫星获得的表层土壤湿度与预期的空间模式一致，很好地识别了沙漠和半干旱地区等已知的干旱地区以及潮湿的农业地区。发现植被光学深度的空间模式与 NDVI 一致。本研究中描述的方法应该可以直接转移到最近发射的 AQUA 卫星上的高级微波扫描辐射计 (AMSR)。
A series of validation studies for a recently developed soil moisture and optical depth retrieval algorithm is presented. The approach is largely theoretical, and uses a non-linear iterative optimization procedure to solve a simple radiative transfer equation for the two parameters from dual polarization satellite microwave brightness temperatures. The satellite retrievals were derived from night-time 6.6 GHz Nimbus Scanning Multichannel Microwave Radiometer (SMMR) observations, and were compared to soil moisture data sets from the USA, Mongolia, Turkmenistan and Russia. The surface temperature, which is also an unknown parameter in the model, is derived off-line from 37 GHz vertical polarized brightness temperatures. The new theoretical approach is independent of field observations of soil moisture or canopy biophysical measurements and can be used at any wavelength in the microwave region. The soil moisture retrievals compared well with the surface moisture observations from the various locations. The vegetation optical depth also compared well to time series of Normalized Difference Vegetation Index (NDVI) and showed similar seasonal patterns. From a global perspective, the satellite-derived surface soil moisture was consistent with expected spatial patterns, identifying both known dry areas such as deserts and semi-arid areas and moist agricultural areas very well. Spatial patterns of vegetation optical depth were found to be in agreement with NDVI. The methodology described in this study should be directly transferable to the Advanced Microwave Scanning Radiometer (AMSR) on the recently launched AQUA satellite.