Advances in Earth Science ›› 2014, Vol. 29 ›› Issue (2): 295-305. doi: 1001-8166(2014)02-0295-11

• Orginal Article • Previous Articles     Next Articles

Soil Moisture Retrieval from Airborne PLMR and MODIS Productsinthe ZhangyeOasisof MiddleStream ofHeihe River Basin, China

Li Dazhi 1, 2, 3, Jin Rui 1, 3, *, Che Tao 1, 3, Walker Jeffrey 4, Gao Ying 4, Ye Nan 5, Wang Shuguo 1, 3   

  1. 1.Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
    2.University of Chinese Academy of Sciences, Beijing 100049, China
    3.Heihe Remote Sensing Experimental Research Station, CAREERI, CAS,Lanzhou 730000, China
    4.Monash University, Department of Civil Engineering, Melbourne 3800, Australia
    5.Nanjing University, Department ofGeographical Information Science, Nanjing 210093,China
  • Received:2013-12-18 Revised:2014-01-23 Online:2014-03-10 Published:2014-02-10
  • Contact: Jin Rui E-mail:lidazhi@lzb.ac.cn;jinrui@lzb.ac.cn

Li Dazhi, Jin Rui, Che Tao, Walker Jeffrey, Gao Ying, Ye Nan, Wang Shuguo. Soil Moisture Retrieval from Airborne PLMR and MODIS Productsinthe ZhangyeOasisof MiddleStream ofHeihe River Basin, China[J]. Advances in Earth Science, 2014, 29(2): 295-305.

Soil moisture is one of important variables in the climate and hydrology research. Remote sensing can map the soil moisture distribution at regional or global scale. Microwave remote sensing now has been the main method to retrieve soil moisture information, especially using satellite-based passive microwave radiometer. L-band is most suitable for the microwave remote sensing of soil moisture due to its longer wavelength. ESA#cod#x02019;s Soil Moisture and Ocean Salinity (SMOS) satellite uses MIRAS (Microwave Imaging Radiometer by Aperture Synthesis) to get multi-angle and dualpolarized brightness temperatures of land surface at L-band. SMOS aims to get global surface soil moisture through radiative transfer model (L-MEB) and multiparameter retrieval method. SMOS Level 2 surface soil moisture algorithm uses an iterative method to minimize a cost function formulated by difference between modeled and measured brightness temperature.PLMR (Polarimetric L-band Multibeam Radiometer) is an airborne simulator of SMOS MIRAS that can measure passive microwave radiation of land surface at L-band (1.4 GHz) dual polarization and in three different angles(7#cod#x000b0;,21.5#cod#x000b0; and 38.5#cod#x000b0;).This paper uses airborne PLMR radiometer data combined with MODIS LST (MOD11A1) and LAI (MOD15A2) products to retrieve surface soil moisture in the artificial oasis experimental area of HiWATER by L-MEB radiative transfer model and LM (Levenberg-Marquardt) optimization algorithm. The three retrieving strategies are tested, including single, two and three parameters selected from soil moisture, vegetation water content and surface roughness. The comparison analysis shows the multi-angle and dual-polarized PLMR brightness temperatures combined with prior information from operational remote sensing products can obviously reduce the uncertainty of retrieval process and improve the retrieval accuracy. This paper proves that with reasonable model parameters and retrieval method, the L-MEB model can achieve 0.04 cm3/cm3 accuracy requirement for soil moisture retrieval. This paper also reveals the importance of using wireless sensor network in the verification of remote sensing products.

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