| 东北典型林区雪深反演算法的验证与分析 |
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| 引用本文： | 武黎黎,李晓峰,赵凯,郑兴明,戴礼云.东北典型林区雪深反演算法的验证与分析[J].地球信息科学,2014(2):320-327. |
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| 作者姓名： | 武黎黎 李晓峰 赵凯 郑兴明 戴礼云 |
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| 作者单位： | [1]中国科学院东北地理与农业生态研究所,长春130102 [2]中国科学院大学,北京100049 [3]中国科学院长春净月潭遥感试验站,长春130102 [4]中国科学院寒区旱区环境与工程研究所,兰州730000 |
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| 基金项目： | 国家自然科学基金项目“东北地区季节性积雪层中雪粒径的谱分布特征与微波（辐射、散射）特性研究”（41001201）;国家高技术研究发展计划（“863计划”）“遥感产品真实性检验关键技术及其试验验证”（2012AA12A305-5-2）. |
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| 摘 要： | 积雪对自然环境和人类活动都有极其重要的影响。积雪参数(雪面积、雪深和雪水当量)反演对水文模型和气候变化研究有着实际的意义。然而,目前森林区的雪深遥感反演精度一直有待于进一步提高。东北地区是我国最大的天然林区和重要的季节性积雪区之一,本文利用FY3B卫星微波成像仪(MWRI)L1级亮温数据和L2级雪水当量数据,以及东北典型林区野外实测雪深数据,对Chang算法、NASA 96算法和FY3B雪深业务化反演算法进行了验证与分析。结果表明:在东北典型林区的雪深反演中,Chang算法和NASA 96算法反演的雪深波动都比较大,当森林覆盖度f≤0.6时,NASA 96算法表现比较好,均方根误差值在3种算法中较小,但当f0.6时,NASA 96算法失真严重。当考虑纯森林像元(f=1)时,Chang算法低估了雪深47%。当f≤0.3时,FY3B业务化算法始终优于Chang算法。整体上,FY3B业务化算法相对稳定,具有较高的精度。
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| 关 键 词： | 积雪 微波遥感 雪深反演 FYB-MWRI |
Validation and Analysis of Snow Depth Inversion Algorithm in Northeast Typical Forest Based on the FY3B-MWRI Data |
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| 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].Geo-information Science,2014(2):320-327. |
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| Authors: | WU Lili LI Xiaofeng ZHAO Kai ZHENG Xingming DAI Liyun |
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| Institution: | 1. Northeast Institute of Geography and Agroecology, CAS, Changchun 130102, China; 2. University of Chinese Academy of Sciences, Beij＇ing 100049, China; 3. Changchun Jingyuetan Remote Sensing Test Site of Chinese Academy of Sciences, Changchun 130102, China;4. Cold and Arid Regions Environmental and Engineering Research Institute, CAS, Lanzhou 730000, China) |
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| Abstract: | Snow cover is one of the active components of the cryosphere. Snow cover has a very important im-pact 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 re-sults 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 algo-rithm had serious distortion when f was bigger than 0.6. Considering the pure forest pixel （ f=1）, Chang algo-rithm 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 opera-tional algorithm had higher accuracy compared with Chang algorithm and NASA 96 algorithm. |
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| Keywords: | FY3B-MWRI snow cover microwave remote sensing snow depth inversion FY3B-MWRI |
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