| 用星载先进微波探测器（AMSU）资料开展区域地表洪涝分类监测 |
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| 引用本文： | 谷松岩,邱红,等.用星载先进微波探测器（AMSU）资料开展区域地表洪涝分类监测[J].应用气象学报,2003,14(1):8-16. |
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| 作者姓名： | 谷松岩 邱红 |
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| 作者单位： | 1.国家卫星气象中心，北京 100081 |
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| 基金项目： | 国家重点基础研究项目 (G1 9980 40 90 9) |
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| 摘 要： | 以微波辐射传输模式为基础，正演模拟分析星载先进微波探测器（AMSU）窗区通道微波亮温对地表洪涝信息的敏感性，结果表明中心频点分别为31.4、50.3和89.0 GHz的AMSU窗区通道2、3和15的微波亮温对地表洪涝特征敏感；以正演模拟计算结果为基础，选择对地表洪涝特征敏感的AMSU窗区通道为因子，组合形成AMSU洪涝指数AFI(AMSU Flooding Index)，进行地表洪涝区分类研究；地表洪涝分类结果与经机-地校验过的机载合成孔径雷达L-SAR资料分析结果进行对比分析，分类正确率可达73%。短时监测试验结果表明，应用美国第5代极轨业务环境卫星上装载的先进微波探测器（AMSU）微波资料可以在准全天候条件下，实现区域地表洪涝区分类实时监测，有效弥补红外和可见波段洪涝遥感探测技术在云天条件下无法实施的缺陷。
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| 关 键 词： | 先进微波探测器 洪涝指数 分类监测 |
| 收稿时间： | 2001-11-28 |
Flood Detection and Monitoring by Use of AMSU-A Microwave Data |
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| Gu Songyan,Qiu Hong,Ran Maonong,Zhang Wenjian.Flood Detection and Monitoring by Use of AMSU-A Microwave Data[J].Quarterly Journal of Applied Meteorology,2003,14(1):8-16. |
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| Authors: | Gu Songyan Qiu Hong Ran Maonong Zhang Wenjian |
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| Affiliation: | 1.National Satellite Meteorological Center , CMA Beijing 1000812.Pek ing University , Beijing 100871 |
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| Abstract: | The Advanced Microwave Sounding Unit A (AMSU A) is a new advanced generation microwave sounding unit, and has great potential in land characteristic analysis, especially on flood detection and monitoring. The wetness index analysis method of flood detection and monitoring by using AMSU A microwave data was tested over Boyang and Tongting lake areas in China during the 1998 summer. To accomplish this, the characteristics of microwave radiance transfer about AMSU A channels are analyzed first and the result indicates that the window channels of AMUS A can give more information about the surface flooding. Then a set of wetness indexes by combining three channels out of four AMSU A window channels (ch1, ch2, ch3, & ch15) is developed. Thereafter the best wetness index which is sensitive to the land surface wetness changes is chosen to conduct the detection and monitoring, and the flooding area is classified into four situations: flooding, mudding, over wet, and background dry area. In the Cal/Val Test, the data from China L SAR aboard on the plane and Canadian Radar SAR aboard on the Radarsat are used, and the Cal/Val results is up to 73%. The future work will focus on the possible improvements in the algorithm and extend testing of the algorithm to other regions. |
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| Keywords: | New type of microwave sounding data Surface wetness index Flood area classification |
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