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Remote Sensing Technology and Application  2020, Vol. 35 Issue (1): 65-73    DOI: 10.11873/j.issn.1004-0323.2020.1.0065
    
Study on Retrieval Strategy of SMOS Soil Moisture Retrieval Algorithm
Congkun Lao(),Na Yang(),Shaobo Xu,Yanjie Tang,Hengjie Zhang
School of Surveying and Land Information Engineering,Henan Polytechnic University, Jiaozuo 454000, China
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Abstract  

In order to reduce the complexity of SMOS official soil moisture retrieval algorithm and improve the accuracy of soil moisture retrievals, a new retrieval strategy on SMOS soil moisture retrieval algorithm was developed. In the new retrieval strategy on SMOS soil moisture retrieval algorithm, the fixed step size (0.001 m3/m3) was used to replace the flexible step size obtained by the SMOS matrix operation. The multi-parameter was changed to a single-parameter in the cost function. The data from 44 USCRN sites in the United States were compared with the soil moisture retrieved from SMOS official algorithm as well as the adjustment of SMOS algorithm. The results show that compared with the SMOS official algorithm, the average absolute deviation, root mean square error,and unbiased root mean square error of the adjustment of SMOS algorithm are reduced by 0.012 m3/m3, 0.018 m3/m3,and 0.020 m3/m3,respectively.

Key words:  Soil moisture      SMOS      Inversion algorithm      Brightness temperature simulation     
Received:  09 December 2019      Published:  01 April 2020
ZTFLH:  TP701  
Corresponding Authors:  Na Yang     E-mail:  lck920911@foxmail.com;yangna800522@foxmail.com
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Congkun Lao
Na Yang
Shaobo Xu
Yanjie Tang
Hengjie Zhang

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Congkun Lao,Na Yang,Shaobo Xu,Yanjie Tang,Hengjie Zhang. Study on Retrieval Strategy of SMOS Soil Moisture Retrieval Algorithm. Remote Sensing Technology and Application, 2020, 35(1): 65-73.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2020.1.0065     OR     http://www.rsta.ac.cn/EN/Y2020/V35/I1/65

Fig.1  Function of soil moisture and surface roughness[23]
参数名称 参考值
地表反射率 QR=0.0 Np=2.0
土壤粗糙度

CXMVT1/2=0.490 0/0.165 0

CWP1/2/3=0.067 7/-0.000 6/0.004 8

HR_MIN/MAX=0.0/0.5

植被光学厚度与单次散射反照率 低矮植被

τ=0.24 ω =0.0

cl=0.24 a_L=2.33 b_L=0.00

森林植被 τ=0.50 ω =0.08
土壤等效温度 bw0=0.3 w 0 =0.3
Table 1  Parameter values
参数名称 ID 单位
气温 T
降水量 P_CALC mm
太阳辐射 SOLARAD W/m2
表面温度 SUR_TEMP
相对湿度 RH %
土壤水分* SOIL_MOISTURE m3/m3
土壤温度* SOIL_TEMP
Table 2  USCRN observation parameters, hourly
年份 筛选/总量 年份 筛选/总量 年份 筛选/总量
2000 0/2 2006 0/97 2012 77/222
2001 0/8 2007 0/121 2013 73/222
2002 0/25 2008 0/137 2014 71/223
2003 0/45 2009 23/155 2015 77/153
2004 0/72 2010 36/201 2016 69/155
2005 0/82 2011 52/219 2017 63/156
2018 61/157
Table 3  Site filtering and hourly data
Fig.2  Spatial distribution of the sites used in the study
FROM-GLC 序号 本文
农田 1 低矮植被
草地 3
灌木 4
森林 2 森林
裸地 9 裸地
湿地 5 其他
6
苔原 7
非渗透表面 8
雪/冰 10
Table 4  FROM-GLC surface types and adjustments
总体平均 SMOS 方案一 方案二
MAD 0.112 0.115 0.100
RMSE 0.133 0.132 0.115
ubRMSE 0.087 0.084 0.067
R 2 0.083/max0.529 0.142/max0.889 0.083/max0.458
Table 5  Comparison of soil moisture retrieval accuracy
Fig.3  Soil moisture inversion results at three sites
站点1* 站点2** 站点3***
SMOS/方案一/二 SMOS/方案一/二 SMOS/方案一/二
MAD 0.075/0.052/0.032 0.102/0.084/0.253 0.154/0.238/0.189
RMSE 0.113/0.060/0.037 0.121/0.106/0.267 0.169/0.249/0.203
ubRMSE 0.108/0.049/0.033 0.082/0.103/0.086 0.072/0.071/0.074
R 2 0.000/0.000/0.006 0.003/0.054/0.004 0.611/0.648/0.565
Table 6  Soil moisture inversion results at each site
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