GLOBAL SOIL MOISTURE ESTIMATION USING CYGNSS DATA

被引：1

作者：

Yan, Qingyun ^{[1
,2
]}

Jin, Shuanggen ^{[1
,2
,3
]}

Huang, Weimin ^{[4
]}

Jia, Yan ^{[5
]}

机构：

[1] Nanjing Univ Informat Sci & Technol, Nanjing 210044, Peoples R China

[2] Jiangsu Engn Ctr Collaborat Nav Positioning & Sma, Nanjing 210044, Peoples R China

[3] Chinese Acad Sci, Shanghai Astron Observ, Shanghai 200030, Peoples R China

[4] Mem Univ Newfoundland, St John, NF A1B 3X5, Canada

[5] Nanjing Univ Posts & Telecommun, Nanjing 210023, Peoples R China

来源：

IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2020年

基金：

加拿大自然科学与工程研究理事会;

关键词：

GNSS-R; CYGNSS; soil moisture; SURFACE-ROUGHNESS;

D O I：

10.1109/IGARSS39084.2020.9323145

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, an approach for estimating soil moisture (SM) from Cyclone Global Navigation Satellite System (CYGNSS) data is developed. Here, a three-layer model of air, vegetation cover, and soil is proposed. In application, the surface reflectivity along with its statistics are derived from the CYGNSS data and the ancillary vegetation opacity data are obtained from Soil Moisture Active Passive (SMAP). These variables are adopted for estimating SM using the devised linear regression function. Through comparing with the reference SM data obtained from SMAP, CYGNSS-derived SM demonstrates its satisfactory accuracy and plausible global coverage. The achieved results prove CYGNSS as an efficient complementary tool for global daily SM sensing.

引用

页码：6182 / 6185

页数：4

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