1 September 2017 Comparison of snow depth retrieval algorithm in Northeastern China based on AMSR2 and FY3B-MWRI data
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Abstract
Snow accumulation has a very important influence on the natural environment and human activities. Meanwhile, improving the estimation accuracy of passive microwave snow depth (SD) retrieval is a hotspot currently. Northeastern China is a typical snow study area including many different land cover types, such as forest, grassland and farmland. Especially, there is relatively stable snow accumulation in January every year. The brightness temperatures which are observed by the Advanced Microwave Scanning Radiometer 2 (AMSR2) on GCOM-W1 and FengYun3B Microwave Radiation Imager (FY3B-MWRI) in the same period in 2013 are selected as the study data in the research. The results of snow depth retrieval using AMSR2 standard algorithm and Jiang’s FY operational algorithm are compared in the research. Moreover, to validate the accuracy of the two algorithms, the retrieval results are compared with the SD data observed at the national meteorological stations in Northeastern China. Furthermore, the retrieval SD is also compared with AMSR2 and FY standard SD products, respectively. The root mean square errors (RMSE) results using AMSR2 standard algorithms and FY operational algorithm are close in the forest surface, which are 6.33cm and 6.28cm, respectively. However, The FY operational algorithm shows a better result than the AMSR2 standard algorithms in the grassland and farmland surface. The RMSE results using FY operational algorithm in the grassland and farmland surface are 2.44cm and 6.13cm, respectively.
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Xintong Fan, Xintong Fan, Lingjia Gu, Lingjia Gu, Ruizhi Ren, Ruizhi Ren, Tingting Zhou, Tingting Zhou, } "Comparison of snow depth retrieval algorithm in Northeastern China based on AMSR2 and FY3B-MWRI data", Proc. SPIE 10405, Remote Sensing and Modeling of Ecosystems for Sustainability XIV, 104050I (1 September 2017); doi: 10.1117/12.2271518; https://doi.org/10.1117/12.2271518
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