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《Remote Sensing Technology and Application》 2017-01
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Retrieval of Snow Albedo based on Multi-source Remote Sensing Data

Shao Donghang;Li Hongyi;Wang Jian;Hao Xiaohua;Wang Runke;Ma Yuan;Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences;University of Chinese Academy of Sciences;Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application;State Key Laboratory of Grassland Agro-ecosystems,College of Pastoral Agriculture Science and Technology,Lanzhou University;  
Snow albedo plays important role in global climate system.There are notable data missing and error uncertainties,attributing to the limit of remote sensing technology.Our study for accuracy evaluation of snow albedo retrieve model,to carry out the validation of the snow albedo retrieval algorithm based on the theory of Asymptotic Radiative Transfer(ART),and compare the difference and accuracy of TM/ETM+data and MODIS data in the retrieval of snow albedo.The results show that the snow albedo accuracy is better than that of the MOD10A1 snow albedo by using the ART model,which is obtained by anisotropic correction of snow reflectance:High-resolution remote sensing image is significantly higher than low-resolution remote sensing image in the retrieval of snow albedo:The scale effect has a great impact on the retrieval of snow albedo in the high and cold mountainous regions.
【Fund】: 国家自然科学基金项目(41471358、41471291、41571371)资助
【CateGory Index】: P426.635;P407
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