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An investigation on microwave transmissivity at frequencies of 18.7 and 36.5 GHz for diverse forest

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论文题目: An investigation on microwave transmissivity at frequencies of 18.7 and 36.5 GHz for diverse forest types during snow season
英文论文题目: An investigation on microwave transmissivity at frequencies of 18.7 and 36.5 GHz for diverse forest types during snow season
第一作者: Wang Guangrui
英文第一作者: Wang Guangrui
联系作者: 李晓峰
英文联系作者: X. F. Li
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发表年度: 2021
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英文摘要: Forests have invariably been considered as an obstacle in retrieving land surface parameters from spaceborne passive microwave brightness temperature (T-B) observations. For quantifying the effect of forests on microwave signals, several models have been developed. However, these models rarely reveal the dependence of microwave radiation on forest types, which can hardly meet the needs of high-accuracy retrieval of terrestrial parameters in forested regions. A ground-based microwave radiometric observation experiment was designed to investigate the dependence of microwave radiation on frequency, polarization, and forest type. Downward T-B at 18.7- and 36.5-GHz for horizontal- and vertical-polarization from the forest canopy was measured at 14 sample plots in Northeast China, along with snowpack and forest structural parameters. By providing fits to experimental data, new empirical transmissivity models for three forest types were developed, as a function of woody stem volume and depending on the frequency/polarization. The proposed models give diverse asymptotic transmissivity saturation levels and the corresponding saturation point of woody stem volume for different forest types. Root-mean-square error results between T-B simulations and Advanced Microwave Scanning Radiometer-2 observations are approximately 3-6 K. This study provides an experimental and theoretical reference for further development of inversion models for snow parameters in forested areas.
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英文刊物名称: International Journal of Digital Earth
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参与作者: G. R. Wang, X. F. Li, X. X. Chen, T. Jiang, X. M. Zheng, Y. L. Wei, X. K. Wan and J. Wang
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