Advances in Earth Science ›› 2015, Vol. 30 ›› Issue (6): 668-679. doi: 10.11867/j.issn.1001-8166.2015.06.0668

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Review in Soil Moisture Remote Sensing Estimation Based on Data Assimilation

Lan Xinyu, Guo Ziqi, Tian Ye, Lei Xia, Wang Jie   

  1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
  • Online:2015-06-25 Published:2015-06-25

Lan Xinyu, Guo Ziqi, Tian Ye, Lei Xia, Wang Jie. Review in Soil Moisture Remote Sensing Estimation Based on Data Assimilation[J]. Advances in Earth Science, 2015, 30(6): 668-679.

Soil moisture is one of the critical variables that affect climate. Retrieving large-scale and high-precision soil moisture data with data assimilation technology is an important issue to study soil moisture. Combining with research status at home and abroad in estimating soil moisture, we sum up the major application process of assimilation algorithm in soil moisture, introduce the widely used land surface model which can retrieve the soil moisture, Noah, Common Land Model (CLM), Simple Biosphere Model (SiB2), North productivity simulation model (BEPS), introduce a wide range of soil moisture satellite data sets including the land surface data assimilation system data sets, ASCAT data sets, AMSR-E data sets and SMOS data sets, and finally discuss the problems and development direction of soil moisture in the process of assimilation.

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