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- W2390230260 abstract "Global continuous long-term surface albedo products are of great importance to land surface process and climate modeling research. Problems such as severe data missing and low effective retrieval percentage in the current albedo products made them difficult to meet the requirements of climate modeling perfectly. To solve those problems, this paper made two improvements on MODIS albedo product algorithm. One improvement was to modify the way of composing and selecting enough directional reflectance, which were used for the generation of background BRDF parameters. We assumed that the surface would change little in the same time period during different years. Therefore, all directional reflectance of multi-years for each time period could be used for the composition and selection, in which at least 7 valid directional reflectance for each pixel were used to conduct the BRDF retrieval. Another improvement was the quantitative data fusion between MODIS and AVHRR data, which helped to expand the temporal coverage of albedo products to 30 years. Validation results showed that this new albedo product kept great consistency with the relatively homogeneous SURFRAD site albedos and was almost the same with MODIS snow-free albedo product. These were no spatial or temporal data missing in this new albedo product and the temporal coverage had been greatly improved. Therefore, this new albedo product would be more suitable for the applications of land surface process and climate modeling research." @default.
- W2390230260 created "2016-06-24" @default.
- W2390230260 creator A5072229410 @default.
- W2390230260 date "2015-01-01" @default.
- W2390230260 modified "2023-09-24" @default.
- W2390230260 title "Generation of Global Long-term Albedo Product Based on the Background Knowledge" @default.
- W2390230260 hasPublicationYear "2015" @default.
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