کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4460769 | 1621349 | 2007 | 17 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields](/preview/png/4460769.png)
In the near future, the SMOS (Soil Moisture and Ocean Salinity) mission will provide global maps of surface soil moisture (SM). The SMOS baseline payload is an L-band (1.4 GHz) two dimensional interferometric microwave radiometer which will provide multi-angular and dual-polarization observations. In the framework of the ground segment activities for the SMOS mission an operational SMOS Level 2 Soil Moisture algorithm was developed. The principle of the algorithm is to exploit multi-angular data in order to retrieve simultaneously several surface parameters including soil moisture and vegetation characteristics. The algorithm uses an iterative approach, minimizing a cost function computed from the differences between measured and modelled brightness temperature (TB) data, for all available incidence angles.In the algorithm, the selected forward model is the so-called L-MEB (L-band Microwave Emission of the Biosphere) model which was the result of an extensive review of the current knowledge of the microwave emission of various land covers. This model is a key element in the SMOS L2 algorithm and could be used in future assimilation studies. There is thus a strong need for a reference study, describing the model and its implementation. In order to address these needs a detailed description of soil and vegetation modelling in L-MEB is given in this study. In a second step, the use of L-MEB in soil moisture retrievals is evaluated for several experimental data sets over agricultural crops. Calibrations of the soil and vegetation L-MEB parameters are investigated for corn, soybean and wheat. Over the different experiments, very consistent results are obtained for each vegetation type in terms of calibration and soil moisture retrievals.
Journal: Remote Sensing of Environment - Volume 107, Issue 4, 30 April 2007, Pages 639–655