Soil Moisture Retrival Based on Sentinel-1 Imagery under Sparse Vegetation Coverage
Huang, Shuai1,2; Ding, Jianli1,2; Zou, Jie1,2; Liu, Bohua1,2; Zhang, Junyong1,2; Chen, Wenqian1,2
Corresponding AuthorDing, Jianli
Year Published2019
Abstract in EnglishSoil moisture is an important aspect of heat transfer process and energy exchange between land-atmosphere systems, and it is a key link to the surface and groundwater circulation and land carbon cycles. In this study, according to the characteristics of the study area, an advanced integral equation model was used for numerical simulation analysis to establish a database of surface microwave scattering characteristics under sparse vegetation cover. Thus, a soil moisture retrieval model suitable for arid area was constructed. The results were as follows: (1) The response of the backscattering coefficient to soil moisture and associated surface roughness is significantly and logarithmically correlated under different incidence angles and polarization modes, and, a database of microwave scattering characteristics of arid soil surface under sparse vegetation cover was established. (2) According to the Sentinel-1 radar system parameters, a model for retrieving spatial distribution information of soil moisture was constructed; the soil moisture content information was extracted, and the results were consistent with the spatial distribution characteristics of soil moisture in the same period in the research area. (3) For the 0-10 cm surface soil moisture, the correlation coefficient between the simulated value and the measured value reached 0.8488, which means that the developed retrieval model has applicability to derive surface soil moisture in the oasis region of arid regions. This study can provide method for real-time and large-scale detection of soil moisture content in arid areas.
Keyword in Englishmicrowave remote sensing Sentinel-1 AIEM model soil moisture
CountryPeoples R China
OA Typegold, Green Published, Green Submitted
Indexed BySCI-E
WOS IDWOS:000459941200152
WOS SubjectChemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS Research AreaChemistry ; Engineering ; Instruments & Instrumentation
Source Institution新疆大学
Document Type期刊论文
Affiliation1.Xinjiang Univ, Coll Resources & Environm Sci, Urumqi 830046, Peoples R China;
2.Xinjiang Univ, Minist Educ, Key Lab Oasis Ecol, Urumqi 830046, Peoples R China
Recommended Citation
GB/T 7714
Huang, Shuai,Ding, Jianli,Zou, Jie,et al. Soil Moisture Retrival Based on Sentinel-1 Imagery under Sparse Vegetation Coverage[J]. 新疆大学,2019,19(3).
APA Huang, Shuai,Ding, Jianli,Zou, Jie,Liu, Bohua,Zhang, Junyong,&Chen, Wenqian.(2019).Soil Moisture Retrival Based on Sentinel-1 Imagery under Sparse Vegetation Coverage.SENSORS,19(3).
MLA Huang, Shuai,et al."Soil Moisture Retrival Based on Sentinel-1 Imagery under Sparse Vegetation Coverage".SENSORS 19.3(2019).
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Huang, Shuai]'s Articles
[Ding, Jianli]'s Articles
[Zou, Jie]'s Articles
Baidu academic
Similar articles in Baidu academic
[Huang, Shuai]'s Articles
[Ding, Jianli]'s Articles
[Zou, Jie]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Huang, Shuai]'s Articles
[Ding, Jianli]'s Articles
[Zou, Jie]'s Articles
Terms of Use
No data!
Social Bookmark/Share

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.