| 光谱学与光谱分析 |
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| The Measurement and Retrieval of the Spectral Reflectance of Different Snow Grain Size on Northern Xinjiang, China |
| HAO Xiao-hua1, WANG Jie1,2, WANG Jian1, ZHANG Pu3, HUANG Chun-lin1 |
1. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
3. Urumqi Meteorological Satellite Ground Station, Urumqi 830011, China |
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Abstract The retrieval of snow grain size is one of the important research directions for cryosphere snow remote sensing. In the present study, we designed the measurement plan of different snow grain size by different snow layer. A SVC HR-1024 ground-based spectral radiometer was used for measuring the spectral property of different snow grain size in northern Xinjiang, China. At the same time，the snow grain size and shape were measured by a hand-loupe with scale. Then the DSPP method was used to calculate the equivalent snow grain size. Finally, the asymptotic radiative transfer (ART) theory was applied to retrieve the snow grain size from measured snow spectral reflectance of different snow layer by optimizing the inversion band and the snow grain size factor “b”. The retrieved snow grain size was validated by the measured snow grain size from DSPP method. The results showed that the DSPP method is an effective means of measuring the equivalent snow grain size. However, there is a large deviation of the snow grain size sample in the same snow layer. It is necessary to improve the measurement method of the single snow grain size sample; The study showed that the near-infrared bands are the most effective selection for retrieval of snow grain size. The retrieval algorithm from ART is feasible. When the snow is dry, the authors optimize the inversion band and the snow grain size factor b in the Northern Xinjiang, China. The optimal band wavelength is 1.20 μm and b is 3.62.
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Received: 2012-09-10
Accepted: 2012-11-18
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Corresponding Authors:
HAO Xiao-hua
E-mail: haoxh@lzb.ac.cn
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