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REMOTE SENSING FOR LAND & RESOURCES    2011, Vol. 23 Issue (2) : 53-58     DOI: 10.6046/gtzyyg.2011.02.10
Technology and Methodology |

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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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.
Keywords SPOT-5 image      River network      Knowledge mine      Discrimination factor     
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  TP 722.6

 
Issue Date: 17 June 2011
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GAO Long-hua
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GAO Long-hua,ZHANG Xing-nan.
A Model Analysis Using a Combined Active/Passive Microwave Remote Sensing Approach for Soil Moisture Retrieval[J]. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(2): 53-58.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2011.02.10     OR     https://www.gtzyyg.com/EN/Y2011/V23/I2/53
[1]Shukla J,Mintz Y.Influence of Land-surface Evapotranspiration on the Earth’s Climate[J].Science,1982,215(4539):1498-1501.
[2]Dobson M C,Ulaby F T.Active Microwave Soil Moisture Research[J].IEEE Transactions on Geoscience and Remote Sensing,1986,24(1):23-36.
[3]Engman E T,Chauhan N.Status of Microwave Soil Moisture Measurements with Remote Sensing[J].Remote Sensing of Environment,1995,51(1):189-198.
[4]Njoku E G,Wilson W J.Observations of Soil Moisture Using A Passive and Active Low-frequency Microwave Airborne Sensor During SGP99[J].IEEE Transactions on Geoscience and Remote Sensing,2002,40(12):2659-2673.
[5]Wilson W J,Yueh S H,Dinardo S J,et al.Passive Active L-and S-band (PALS) Microwave Sensor for Ocean Ssalinity and Soil Moisture Measurements[J].IEEE Transactions on Geoscience and Remote Sensing,2001,39(1):1039-1048.
[6]Njoku E G,Wilson W J.A Large-antenna Microwave Radiometer-scatterometer Concept for Ocean Salinity and Soil Moisture Sensing[J].IEEE Transactions on Geoscience and Remote Sensing,2000,38(11):2645-2655.
[7]Lee K H,Anagnostou E N.A Combined Passive/active Microwave Remote Sensing Approach for Surface Variable Retrieval Using Tropical Rainfall Measuring Mission Observations[J].Remote Sensing of Environment,2004,92(7):112-125.
[8]Narayan U.High Resolution Change Estimation of Soil Moisture Using L-Band Radiometer and Radar Observations Made During the SMEX02 Experiments[J].IEEE Transactions on Geoscience and Remote Sensing,2006,44(6):1545-1554.
[9]Dobson M C,Ulaby F T.Active Microwave Soil Moisture Research[J].IEEE Transactions on Geoscience and Remote Sensing,1986,24(1):23-36.
[10]Kummerow C,Barnes W,Kozu T.The Tropical Rainfall Measuring Mission (TRMM) Sensor Package[J].Journal of Atmospheric and Oceanic Technology,1998,15(6):809-817.
[11]Fung A K,Li Z Q,Chen K S.Backscattering from a Randomly Rough Dielectric Surface[J].IEEE Transactions on Geoscience and Remote Sensing,1992,30(2):195-220.
[12]Chen K S,Wu T D,Tsang L,et al.Emission of Rough Surfaces Calculated by the Integral Equation Method with Comparison to Three Dimensional Moment Method Simulations[J].IEEE Transactions on Geoscience and Remote Sensing,2003,41(1):90-101.
[13]Shi J C,Chen K S,Li Q,et al.A Parameterized Surface Reflectivity Model and Estimation of Bare Surface Soil Moisture with L2 Band Radiometer[J].IEEE Transactions on Geoscience and Remote Sensing,2002,40(12):2674-2686.
[14]Shi J C,Jiang L M,Zhang L X.Parameterized Multi-Frequency-Polarization Surface Emission Model[J].Journal of Remote Sensing,2006,10(4):502-513.
[15]Dobson M C,Ulaby F T,Hallikainen M T,et al.Microwave Dielectric Behavior of Wet Soil Part II:Dielectric Mixing Models[J].IEEE Transactions on Geoscience and Remote Sensing,1985,23(1):35-46.
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