北京大学学报(自然科学版)

FY-3A/MWRI数据反演半干旱地区土壤湿度的研究

彭丽春1,2,李万彪1,2,刘辉志2   

  1. 1. 北京大学物理学院大气与海洋科学系, 北京 100871; 2. 中国科学院大气物理研究所大气边界层物理和大气化学国家重点实验室, 北京 100029;
  • 收稿日期:2010-08-27 出版日期:2011-09-20 发布日期:2011-09-20

Estimation of the Soil Moisture Using FY-3A/MWRI Data over Semiarid Areas

PENG Lichun1,2, LI Wanbiao1,2, LIU Huizhi2   

  1. 1. Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871; 2. LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;
  • Received:2010-08-27 Online:2011-09-20 Published:2011-09-20

摘要: 为了监测半干旱地区干旱化范围和干旱程度, 探讨了一种利用卫星微波遥感反演土壤湿度的方法。根据陆表和大气辐射传输模式模拟植被覆盖地表微波亮温和土壤湿度的关系, 建立土壤湿度的对数三次多项式的反演算法。利用中国气象卫星(FY-3A)搭载的微波成像仪(MWRI)的亮温资料,反演得到吉林通榆地区农田和草地的土壤湿度, 并与地面实测结果进行对比, 其均方根误差农田为0.003 cm3/cm3, 草地为0.005 cm3/cm3, 反演精度较高。本方法可以应用于可以获得更多资料的FY-3B卫星, 结合改进的辐射传输模式获取不同地表类型的辐射特征, 期望未来可进行区域试验的反演研究。

关键词: FY-3A/MWRI, 归一化植被指数(NDVI)?, 亮温极化比, 土壤湿度

Abstract: In order to monitor the range and extent of drought and resolve the serious problems of the semi-arid regions, a soil moisture retrieval method by satellite microwave remote sensing is proposed. The relation of microwave brightness temperature and surface soil moisture was simulated by surface and atmosphere microwave radiative transfer models. The soil moisture retrieval algorithm in the logarithm-cubic form was established. By using the data of the microwave radiation imager aboard the FY-3A polar orbiting meteorological satellite and the retrieval algorithm, the soil moisture was derived for the farmland and the grassland in Tongyu of Jilin. The result shows that the retrieval soil moisture is in good agreement with the ground-based observations. The root mean square error is 0.003 cm3/cm3 for the farmland, and 0.005 cm3/cm3 for grassland. The method can be applied to the future FY-3B satellite that is possible to derive more information. With the improved radiation transfer model in the future, the radiation characteristics of the various grounds will be obtained. The regional moisture study will be carried on in the future.

Key words: FY-3A/MWRI, normalized difference vegetation index(NDVI), brightness temperature polarization ration, soil moisture

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