Journal of Geo-information Science >
Validation and Analysis of Snow Depth Inversion Algorithm in Northeast Typical Forest Based on the FY3B-MWRI Data
Received date: 2013-04-12
Revised date: 2013-05-16
Online published: 2014-03-10
Snow cover is one of the active components of the cryosphere. Snow cover has a very important impact on the natural environment and human activities. Snow parameters (snow area, snow depth and snow water equivalent) inversion has practical significance to hydrological models and climate change research. However, the accuracy of snow depth inversion of remote sensing in the forest area should be further improved at present. Northeast is one of China's largest natural forest areas and important seasonal snow areas. This paper used L1 level brightness temperature data and L2 level snow water equivalent data of Microwave Radiation Imager (MWRI) mounted on FY3B satellite, and used field snow depth data in Northeast typical forest regions. Chang algorithm, NASA 96 algorithm and FY3B operational inversion algorithm were validated and analyzed. The results showed that, in Northeast typical forest regions, the retrieved snow depth of Chang algorithm and NASA 96 algorithm had large fluctuations. The performance of NASA 96 algorithm was better than Chang algorithm and FY3B operational inversion algorithm when fractional forest cover (f) was 0.6 or less, because the root mean square error value of NASA 96 algorithm was smaller than the other two algorithms. However, NASA96 algorithm had serious distortion when f was bigger than 0.6. Considering the pure forest pixel (f=1), Chang algorithm underestimated the snow depth of 47%. When f was 0.3 or less, FY3B operational inversion algorithm is better than Chang algorithm. On the whole, FY3B operational algorithm was relatively stable, and FY3B operational algorithm had higher accuracy compared with Chang algorithm and NASA 96 algorithm.
Key words： microwave remote sensing; FY3B-MWRI; snow depth inversion; snow cover
WU Lili, LI Xiaofeng, ZHAO Kai, ZHENG Xingming, DAI Liyun . Validation and Analysis of Snow Depth Inversion Algorithm in Northeast Typical Forest Based on the FY3B-MWRI Data[J]. Journal of Geo-information Science, 2014 , 16(2) : 320 -327 . DOI: 10.3724/SP.J.1047.2014.00320
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