Modeling Microwave Emission from Short Vegetation-Covered Surfaces
AbstractOwing to the temporal and spatial variability of the emissivity spectra, problems remain in the interpretation and application of satellite passive microwave data over vegetation-covered surfaces. The commonly used microwave land emissivity model, developed by Weng et al. (2001) and implemented into the community radiative transfer model (CRTM), treats vegetation-covered surfaces as a three-layer medium. This simplification comes at the cost of accuracy. In this study, to reduce bias in the modeling of microwave emissions from short vegetation-covered surfaces, two modifications are made. First, vegetation was considered as a multilayered medium including leaves and stems to simulate volumetric absorption and scattering. The results suggest that the calculated brightness temperatures well agree with field experiments under different incidence angles for low soil moisture and sparse crop cover. On the other hand, large errors from the measurements are found for high soil moisture content and dense crop cover. Second, the advanced integral equation model (AIEM) was also used to improve the simulation of reflectivity from rough soil surfaces. Comparisons with field experimental data show that the determination coefficient between the calculated and measured brightness temperatures significantly increased and the root-mean-square errors remarkably decreased. The average improvement using the proposed approach is about 80% and 59% in accuracy for the vertical and horizontal polarization, respectively. View Full-Text
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Xie, Y.; Shi, J.; Lei, Y.; Li, Y. Modeling Microwave Emission from Short Vegetation-Covered Surfaces. Remote Sens. 2015, 7, 14099-14118.
Xie Y, Shi J, Lei Y, Li Y. Modeling Microwave Emission from Short Vegetation-Covered Surfaces. Remote Sensing. 2015; 7(10):14099-14118.Chicago/Turabian Style
Xie, Yanhui; Shi, Jiancheng; Lei, Yonghui; Li, Yunqing. 2015. "Modeling Microwave Emission from Short Vegetation-Covered Surfaces." Remote Sens. 7, no. 10: 14099-14118.