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L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields
- Source :
-
Remote Sensing of Environment . Apr2007, Vol. 107 Issue 4, p639-655. 17p. - Publication Year :
- 2007
-
Abstract
- 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 (T B) 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. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 00344257
- Volume :
- 107
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Remote Sensing of Environment
- Publication Type :
- Academic Journal
- Accession number :
- 24612346
- Full Text :
- https://doi.org/10.1016/j.rse.2006.10.014