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国土资源遥感  2011, Vol. 23 Issue (2): 53-58    DOI: 10.6046/gtzyyg.2011.02.10
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
利用主被动微波遥感结合反演土壤水分的理论模型分析
杨立娟1, 武胜利2, 张钟军1,3
1.北京师范大学信息科学与技术学院,北京100875; 2.中国气象局国家卫星气象中心,北京100081; 3.遥感科学国家重点实验室,北京100875

A Model Analysis Using a Combined Active/Passive Microwave Remote Sensing Approach for Soil Moisture Retrieval
YANG Li-juan 1, WU Sheng-li 2, ZHANG Zhong-jun 1,3
1.College of Information Science and Technology, Beijing Normal University, Beijing 100875, China; 2.The National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China; 3.State Key Laboratory of Remote Sensing Science, Beijing 100875, China
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摘要 为了更好地进行土壤水分反演,发展了一种基于热带降雨观测计划(TRMM)的主被动微波结合反演裸露地表土壤水分的算法。为了提高反演精度,同时利用TRMM搭载的测雨雷达(PR)和微波成像仪(TMI)进行观测。另外,针对PR/TMI数据,还建立了包含大范围的土壤水分和粗糙度参数的AIEM模型数据库。通过分析AIEM模型对地表后向散射和辐射的模拟发现,地表粗糙度参数对后向散射系数和亮温均有重要的影响。最后,在AIEM模型模拟数据库的基础上,利用理论模型——几何光学模型(GO模型)和半经验模型——Qp模型,通过对地表粗糙度参数的分析,结合TRMM/PR和TMI数据,建立了一种主被动微波遥感相结合的反演裸露地表土壤水分的模型,并进一步获得了反演土壤水分的算法。
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高龙华
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关键词 SPOT-5图像河网知识挖掘判别因子    
Abstract:This study develops a new algorithm for estimating bare surface soil moisture using combined active/passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). To accurately estimate bare surface soil moisture, the algorithm simultaneously uses a precipitation radar (PR) and microwave imager (TMI) for observation. In this paper, through an analysis of the numerically simulated surface backscattering and emissivity database by Advanced Integral Equation Model (AIEM) with a wide range of soil moisture and surface roughness conditions,the authors have found that the surface roughness parameter has an important impact on both backscattering coefficient and emissivity. Based on the simulated database by AIEM, the authors use theoretical model (Geometrical Optical Model) and semi-empirical model (Qp Model) through the analysis of surface roughness as well as TRMM/PR and TMI data to develop the algorithm for estimating bare surface soil moisture.
Key wordsSPOT-5 image    River network    Knowledge mine    Discrimination factor
收稿日期: 2010-07-16      出版日期: 2011-06-17
: 

 

 
  TP 722.6

 
基金资助:

国家自然科学基金项目“基于模型融合的主被动微波遥感反演土壤水分算法研究”(编号40801132); 国家重点基础研究发展计划“973”项目(编号: 2007CB714403)。

作者简介: 杨立娟(1985-),女,现为北京师范大学通信与信息系统专业硕士研究生,主要从事微波遥感方面的研究。
引用本文:   
杨立娟, 武胜利, 张钟军. 利用主被动微波遥感结合反演土壤水分的理论模型分析[J]. 国土资源遥感, 2011, 23(2): 53-58.
YANG Li-Juan, WU Sheng-Li, ZHANG Zhong-Jun.
A Model Analysis Using a Combined Active/Passive Microwave Remote Sensing Approach for Soil Moisture Retrieval. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(2): 53-58.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2011.02.10      或      https://www.gtzyyg.com/CN/Y2011/V23/I2/53
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